-<body>\r
-<title>IMaCh Cov rbiaspar.txt</title>\r
- <font size="2">Imach version 0.07a, May 2004, INED-EUROREVES <br> $Revision$ $Date$</font> <hr size="2" color="#EC5E5E"> \r
-Title=1st_example <br>Datafile=data1.txt Firstpass=1 Lastpass=4 Stepm=1 Weight=0 Model=.<br>\r
-\r
-<h4>Matrix of variance-covariance of pairs of step probabilities</h4>\r
- file biaspar-cov.htm<br>\r
-\r
-Ellipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimatedand drawn. It helps understanding how is the covariance between two incidences. They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\r
-\r
-<br> Contour plot corresponding to x'cov<sup>-1</sup>x = 4 (where x is the column vector (pij,pkl)) are drawn. It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 standard deviations wide on each axis. <br> Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix and made the appropriate rotation to look at the uncorrelated principal directions.<br>To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \r
-\r
-<br>Ellipsoids of confidence cov(p13,p12) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar113-12.png">biaspar/varpijgrbiaspar113-12.png</A>, \r
-<br><img src="biaspar/varpijgrbiaspar113-12.png"> \r
-<br> Correlation at age 65 (-0.365), 70 (-0.388), 75 (-0.431), 80 (-0.475), 85 (-0.419), 90 (-0.360), 95 (-0.346),\r
-<br>Ellipsoids of confidence cov(p21,p12) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar121-12.png">biaspar/varpijgrbiaspar121-12.png</A>, \r
-<br><img src="biaspar/varpijgrbiaspar121-12.png"> \r
-<br> Correlation at age 65 (0.346), 70 (0.341), 75 (0.328), 80 (0.297), 85 (0.283), 90 (0.316), 95 (0.332),\r
-<br>Ellipsoids of confidence cov(p23,p12) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar123-12.png">biaspar/varpijgrbiaspar123-12.png</A>, \r
-<br><img src="biaspar/varpijgrbiaspar123-12.png"> \r
-<br> Correlation at age 65 (0.367), 70 (0.390), 75 (0.426), 80 (0.453), 85 (0.359), 90 (0.257), 95 (0.241),\r
-<br>Ellipsoids of confidence cov(p21,p13) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar121-13.png">biaspar/varpijgrbiaspar121-13.png</A>, \r
-<br><img src="biaspar/varpijgrbiaspar121-13.png"> \r
-<br> Correlation at age 65 (0.034), 70 (0.024), 75 (0.012), 80 (0.017), 85 (0.080), 90 (0.103), 95 (0.096),\r
-<br>Ellipsoids of confidence cov(p23,p13) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar123-13.png">biaspar/varpijgrbiaspar123-13.png</A>, \r
-<br><img src="biaspar/varpijgrbiaspar123-13.png"> \r
-<br> Correlation at age 65 (-0.456), 70 (-0.492), 75 (-0.552), 80 (-0.594), 85 (-0.523), 90 (-0.456), 95 (-0.404),\r
-<br>Ellipsoids of confidence cov(p23,p21) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar123-21.png">biaspar/varpijgrbiaspar123-21.png</A>, \r
-<br><img src="biaspar/varpijgrbiaspar123-21.png"> \r
-<br> Correlation at age 65 (-0.025), 70 (-0.022), 75 (-0.020), 80 (-0.027), 85 (-0.060), 90 (-0.077), 95 (-0.065),
\ No newline at end of file
+<body>
+<title>IMaCh Cov rbiaspar.txt</title>
+ <font size="2">Imach version 0.98, September 2005, INED-EUROREVES <br> $Revision$ $Date$</font> <hr size="2" color="#EC5E5E">
+Title=1st_example <br>Datafile=data1.txt Firstpass=1 Lastpass=4 Stepm=1 Weight=0 Model=.<br>
+
+<h4>Matrix of variance-covariance of pairs of step probabilities</h4>
+ file biaspar-cov.htm<br>
+
+Ellipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimatedand drawn. It helps understanding how is the covariance between two incidences. They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>
+
+<br> Contour plot corresponding to x'cov<sup>-1</sup>x = 4 (where x is the column vector (pij,pkl)) are drawn. It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 standard deviations wide on each axis. <br> Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix and made the appropriate rotation to look at the uncorrelated principal directions.<br>To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br>
+
+<br>Ellipsoids of confidence cov(p13,p12) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar113-12.png">biaspar/varpijgrbiaspar113-12.png</A>,
+<br><img src="biaspar/varpijgrbiaspar113-12.png">
+<br> Correlation at age 65 (-0.393), 70 (-0.413), 75 (-0.448), 80 (-0.477), 85 (-0.422), 90 (-0.376), 95 (-0.369),
+<br>Ellipsoids of confidence cov(p21,p12) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar121-12.png">biaspar/varpijgrbiaspar121-12.png</A>,
+<br><img src="biaspar/varpijgrbiaspar121-12.png">
+<br> Correlation at age 65 (0.317), 70 (0.314), 75 (0.307), 80 (0.290), 85 (0.281), 90 (0.298), 95 (0.306),
+<br>Ellipsoids of confidence cov(p23,p12) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar123-12.png">biaspar/varpijgrbiaspar123-12.png</A>,
+<br><img src="biaspar/varpijgrbiaspar123-12.png">
+<br> Correlation at age 65 (0.380), 70 (0.402), 75 (0.435), 80 (0.456), 85 (0.358), 90 (0.266), 95 (0.256),
+<br>Ellipsoids of confidence cov(p21,p13) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar121-13.png">biaspar/varpijgrbiaspar121-13.png</A>,
+<br><img src="biaspar/varpijgrbiaspar121-13.png">
+<br> Correlation at age 65 (0.029), 70 (0.021), 75 (0.010), 80 (0.018), 85 (0.079), 90 (0.099), 95 (0.091),
+<br>Ellipsoids of confidence cov(p23,p13) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar123-13.png">biaspar/varpijgrbiaspar123-13.png</A>,
+<br><img src="biaspar/varpijgrbiaspar123-13.png">
+<br> Correlation at age 65 (-0.473), 70 (-0.506), 75 (-0.561), 80 (-0.595), 85 (-0.519), 90 (-0.461), 95 (-0.418),
+<br>Ellipsoids of confidence cov(p23,p21) expressed in year<sup>-1</sup> :<a href="biaspar/varpijgrbiaspar123-21.png">biaspar/varpijgrbiaspar123-21.png</A>,
+<br><img src="biaspar/varpijgrbiaspar123-21.png">
+<br> Correlation at age 65 (-0.027), 70 (-0.023), 75 (-0.021), 80 (-0.028), 85 (-0.059), 90 (-0.076), 95 (-0.064),
\ No newline at end of file
-\r
-# Imach version 0.07a, May 2004, INED-EUROREVES \r
-# biaspar.gp\r
-set missing 'NaNq'\r
-cd "D:/imachcvs/imach/html/doc/" \r
-\r
-set out "biaspar/vbiaspar11.png" \r
-\r
-#set out "vbiaspar11.png" \r
-set xlabel "Age" \r
-set ylabel "Probability" \r
-set ter png small\r
-set size 0.65,0.65\r
-plot [70:95] "biaspar/vplrbiaspar.txt" every :::0::0 u 1:2 "%lf %lf (%lf) %*lf (%*lf)" t"Stable prevalence" w l 0,"biaspar/vplrbiaspar.txt" every :::0::0 u 1:($2+1.96*$3) "%lf %lf (%lf) %*lf (%*lf)" t"95% CI" w l 1,"biaspar/vplrbiaspar.txt" every :::0::0 u 1:($2-1.96*$3) "%lf %lf (%lf) %*lf (%*lf)" t"" w l 1,"biaspar/prbiaspar.txt" every :::0::0 u 1:($2) t"Observed prevalence " w l 2\r
-set out "biaspar/vbiaspar21.png" \r
-\r
-#set out "vbiaspar21.png" \r
-set xlabel "Age" \r
-set ylabel "Probability" \r
-set ter png small\r
-set size 0.65,0.65\r
-plot [70:95] "biaspar/vplrbiaspar.txt" every :::0::0 u 1:2 "%lf %*lf (%*lf) %lf (%lf)" t"Stable prevalence" w l 0,"biaspar/vplrbiaspar.txt" every :::0::0 u 1:($2+1.96*$3) "%lf %*lf (%*lf) %lf (%lf)" t"95% CI" w l 1,"biaspar/vplrbiaspar.txt" every :::0::0 u 1:($2-1.96*$3) "%lf %*lf (%*lf) %lf (%lf)" t"" w l 1,"biaspar/prbiaspar.txt" every :::0::0 u 1:($6) t"Observed prevalence " w l 2\r
-set out "biaspar/ebiaspar1.png" \r
-set ylabel "Years" \r
-set ter png small\r
-set size 0.65,0.65\r
-plot [70:95] "biaspar/trbiaspar.txt" every :::0::0 u 1:2 "%lf %lf (%lf) %*lf (%*lf) %*lf (%*lf)" t"TLE" w l ,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2-$3*2) "%lf %lf (%lf) %*lf (%*lf) %*lf (%*lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2+$3*2) "%lf %lf (%lf) %*lf (%*lf) %*lf (%*lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:2 "%lf %*lf (%*lf) %lf (%lf) %*lf (%*lf)" t"LE in state (1)" w l ,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2-$3*2) "%lf %*lf (%*lf) %lf (%lf) %*lf (%*lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2+$3*2) "%lf %*lf (%*lf) %lf (%lf) %*lf (%*lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:2 "%lf %*lf (%*lf) %*lf (%*lf) %lf (%lf)" t"LE in state (2)" w l ,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2-$3*2) "%lf %*lf (%*lf) %*lf (%*lf) %lf (%lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2+$3*2) "%lf %*lf (%*lf) %*lf (%*lf) %lf (%lf)" t"" w l 0\r
-set out "biaspar/expbiaspar11.png" \r
-set ter png small\r
-set size 0.65,0.65\r
-plot [70:95] "biaspar/erbiaspar.txt" every :::0::0 u 1:2 t "e11" w l ,"biaspar/erbiaspar.txt" every :::0::0 u 1:4 t "e12" w l\r
-set out "biaspar/expbiaspar21.png" \r
-set ter png small\r
-set size 0.65,0.65\r
-plot [70:95] "biaspar/erbiaspar.txt" every :::0::0 u 1:6 t "e21" w l ,"biaspar/erbiaspar.txt" every :::0::0 u 1:8 t "e22" w l\r
-set out "biaspar/pbiaspar11.png" \r
-set xlabel "Age" \r
-set ylabel "Probability" \r
-set ter png small\r
-set size 0.65,0.65\r
-unset log y\r
-plot [70:95] "biaspar/pijrbiaspar.txt" u ($1==1 ? ($3):1/0):($5/($4+$5)) t"prev(1,2)" w l,"biaspar/pijrbiaspar.txt" u ($1==1 ? ($3):1/0):($8/($7+$8)) t"prev(2,2)" w l\r
-\r
-set out "biaspar/pbiaspar21.png" \r
-set xlabel "Age" \r
-set ylabel "Probability" \r
-set ter png small\r
-set size 0.65,0.65\r
-unset log y\r
-plot [70:95] "biaspar/pijrbiaspar.txt" u ($1==1 ? ($3):1/0):($6/($4+$5)) t"prev(2,3)" w l,"biaspar/pijrbiaspar.txt" u ($1==1 ? ($3):1/0):($12/($10+$11)) t"prev(3,3)" w l\r
-p1=-12.245160 \r
-p2=0.092357 \r
-p3=-10.672078 \r
-p4=0.060971 \r
-p5=-2.645815 \r
-p6=-0.022320 \r
-p7=-4.773208 \r
-p8=0.007857 \r
-\r
-set out "biaspar/pebiaspar11.png" \r
-\r
-set title "Probability"\r
-\r
-set ter png small\r
-set size 0.65,0.65\r
-set log y\r
-plot [70:95] exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)) t "p12" , exp(p3+p4*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)) t "p13" , exp(p5+p6*x)/(1+exp(p5+p6*x)+exp(p7+p8*x)) t "p21" , exp(p7+p8*x)/(1+exp(p5+p6*x)+exp(p7+p8*x)) t "p23" \r
-set out "biaspar/pebiaspar12.png" \r
-\r
-set ylabel "Quasi-incidence per year"\r
-\r
-set ter png small\r
-set size 0.65,0.65\r
-set log y\r
-plot [70:95] 12.000000*exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)) t "p12" , 12.000000*exp(p3+p4*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)) t "p13" , 12.000000*exp(p5+p6*x)/(1+exp(p5+p6*x)+exp(p7+p8*x)) t "p21" , 12.000000*exp(p7+p8*x)/(1+exp(p5+p6*x)+exp(p7+p8*x)) t "p23" \r
-# Routine varprob\r
-set parametric;unset label\r
-set log y;set log x; set xlabel "p13 (year-1)";set ylabel "p12 (year-1)"\r
-set ter png small\r
-set size 0.65,0.65\r
-set out "biaspar/varpijgrbiaspar113-12.png"\r
-set label "65" at 1.459e-002, 2.328e-002 center\r
-# Age 65, p13 - p12\r
-plot [-pi:pi] 1.459e-002+ 2.000*( 6.866e-001* 2.057e-003*cos(t)+ 7.270e-001* 1.402e-003*sin(t)), 2.328e-002 +2.000*(-7.270e-001* 2.057e-003*cos(t)+ 6.866e-001* 1.402e-003*sin(t)) not\r
-# Age 70, p13 - p12\r
-set label "70" at 1.976e-002, 3.688e-002 center\r
-replot 1.976e-002+ 2.000*( 5.191e-001* 2.326e-003*cos(t)+ 8.547e-001* 1.471e-003*sin(t)), 3.688e-002 +2.000*(-8.547e-001* 2.326e-003*cos(t)+ 5.191e-001* 1.471e-003*sin(t)) not\r
-# Age 75, p13 - p12\r
-set label "75" at 2.674e-002, 5.839e-002 center\r
-replot 2.674e-002+ 2.000*( 4.119e-001* 2.525e-003*cos(t)+ 9.112e-001* 1.387e-003*sin(t)), 5.839e-002 +2.000*(-9.112e-001* 2.525e-003*cos(t)+ 4.119e-001* 1.387e-003*sin(t)) not\r
-# Age 80, p13 - p12\r
-set label "80" at 3.614e-002, 9.233e-002 center\r
-replot 3.614e-002+ 2.000*( 3.972e-001* 2.741e-003*cos(t)+ 9.177e-001* 1.382e-003*sin(t)), 9.233e-002 +2.000*(-9.177e-001* 2.741e-003*cos(t)+ 3.972e-001* 1.382e-003*sin(t)) not\r
-# Age 85, p13 - p12\r
-set label "85" at 4.875e-002, 1.457e-001 center\r
-replot 4.875e-002+ 2.000*( 3.964e-001* 4.133e-003*cos(t)+ 9.181e-001* 2.272e-003*sin(t)), 1.457e-001 +2.000*(-9.181e-001* 4.133e-003*cos(t)+ 3.964e-001* 2.272e-003*sin(t)) not\r
-# Age 90, p13 - p12\r
-set label "90" at 6.557e-002, 2.292e-001 center\r
-replot 6.557e-002+ 2.000*( 2.870e-001* 8.981e-003*cos(t)+ 9.579e-001* 4.671e-003*sin(t)), 2.292e-001 +2.000*(-9.579e-001* 8.981e-003*cos(t)+ 2.870e-001* 4.671e-003*sin(t)) not\r
-# Age 95, p13 - p12\r
-set label "95" at 8.778e-002, 3.591e-001 center\r
-replot 8.778e-002+ 2.000*( 2.106e-001* 1.972e-002*cos(t)+ 9.776e-001* 8.813e-003*sin(t)), 3.591e-001 +2.000*(-9.776e-001* 1.972e-002*cos(t)+ 2.106e-001* 8.813e-003*sin(t)) not\r
-set out "biaspar/varpijgrbiaspar113-12.png";replot;\r
-set parametric;unset label\r
-set log y;set log x; set xlabel "p21 (year-1)";set ylabel "p12 (year-1)"\r
-set ter png small\r
-set size 0.65,0.65\r
-set out "biaspar/varpijgrbiaspar121-12.png"\r
-set label "65" at 1.936e-001, 2.328e-002 center\r
-# Age 65, p21 - p12\r
-plot [-pi:pi] 1.936e-001+ 2.000*( 9.998e-001* 3.151e-002*cos(t)+-1.959e-002* 1.668e-003*sin(t)), 2.328e-002 +2.000*( 1.959e-002* 3.151e-002*cos(t)+ 9.998e-001* 1.668e-003*sin(t)) not\r
-# Age 70, p21 - p12\r
-set label "70" at 1.734e-001, 3.688e-002 center\r
-replot 1.734e-001+ 2.000*( 9.994e-001* 2.161e-002*cos(t)+-3.389e-002* 2.001e-003*sin(t)), 3.688e-002 +2.000*( 3.389e-002* 2.161e-002*cos(t)+ 9.994e-001* 2.001e-003*sin(t)) not\r
-# Age 75, p21 - p12\r
-set label "75" at 1.552e-001, 5.839e-002 center\r
-replot 1.552e-001+ 2.000*( 9.983e-001* 1.378e-002*cos(t)+-5.800e-002* 2.235e-003*sin(t)), 5.839e-002 +2.000*( 5.800e-002* 1.378e-002*cos(t)+ 9.983e-001* 2.235e-003*sin(t)) not\r
-# Age 80, p21 - p12\r
-set label "80" at 1.389e-001, 9.233e-002 center\r
-replot 1.389e-001+ 2.000*( 9.949e-001* 8.292e-003*cos(t)+-1.011e-001* 2.447e-003*sin(t)), 9.233e-002 +2.000*( 1.011e-001* 8.292e-003*cos(t)+ 9.949e-001* 2.447e-003*sin(t)) not\r
-# Age 85, p21 - p12\r
-set label "85" at 1.243e-001, 1.457e-001 center\r
-replot 1.243e-001+ 2.000*( 9.669e-001* 6.441e-003*cos(t)+-2.553e-001* 3.657e-003*sin(t)), 1.457e-001 +2.000*( 2.553e-001* 6.441e-003*cos(t)+ 9.669e-001* 3.657e-003*sin(t)) not\r
-# Age 90, p21 - p12\r
-set label "90" at 1.112e-001, 2.292e-001 center\r
-replot 1.112e-001+ 2.000*( 5.879e-001* 9.566e-003*cos(t)+-8.090e-001* 6.788e-003*sin(t)), 2.292e-001 +2.000*( 8.090e-001* 9.566e-003*cos(t)+ 5.879e-001* 6.788e-003*sin(t)) not\r
-# Age 95, p21 - p12\r
-set label "95" at 9.953e-002, 3.591e-001 center\r
-replot 9.953e-002+ 2.000*( 2.290e-001* 1.977e-002*cos(t)+-9.734e-001* 9.572e-003*sin(t)), 3.591e-001 +2.000*( 9.734e-001* 1.977e-002*cos(t)+ 2.290e-001* 9.572e-003*sin(t)) not\r
-set out "biaspar/varpijgrbiaspar121-12.png";replot;\r
-set parametric;unset label\r
-set log y;set log x; set xlabel "p23 (year-1)";set ylabel "p12 (year-1)"\r
-set ter png small\r
-set size 0.65,0.65\r
-set out "biaspar/varpijgrbiaspar123-12.png"\r
-set label "65" at 1.640e-001, 2.328e-002 center\r
-# Age 65, p23 - p12\r
-plot [-pi:pi] 1.640e-001+ 2.000*( 9.995e-001* 2.107e-002*cos(t)+-3.113e-002* 1.654e-003*sin(t)), 2.328e-002 +2.000*( 3.113e-002* 2.107e-002*cos(t)+ 9.995e-001* 1.654e-003*sin(t)) not\r
-# Age 70, p23 - p12\r
-set label "70" at 1.708e-001, 3.688e-002 center\r
-replot 1.708e-001+ 2.000*( 9.988e-001* 1.745e-002*cos(t)+-4.823e-002* 1.959e-003*sin(t)), 3.688e-002 +2.000*( 4.823e-002* 1.745e-002*cos(t)+ 9.988e-001* 1.959e-003*sin(t)) not\r
-# Age 75, p23 - p12\r
-set label "75" at 1.778e-001, 5.839e-002 center\r
-replot 1.778e-001+ 2.000*( 9.971e-001* 1.368e-002*cos(t)+-7.559e-002* 2.139e-003*sin(t)), 5.839e-002 +2.000*( 7.559e-002* 1.368e-002*cos(t)+ 9.971e-001* 2.139e-003*sin(t)) not\r
-# Age 80, p23 - p12\r
-set label "80" at 1.851e-001, 9.233e-002 center\r
-replot 1.851e-001+ 2.000*( 9.925e-001* 1.009e-002*cos(t)+-1.220e-001* 2.279e-003*sin(t)), 9.233e-002 +2.000*( 1.220e-001* 1.009e-002*cos(t)+ 9.925e-001* 2.279e-003*sin(t)) not\r
-# Age 85, p23 - p12\r
-set label "85" at 1.926e-001, 1.457e-001 center\r
-replot 1.926e-001+ 2.000*( 9.722e-001* 7.671e-003*cos(t)+-2.342e-001* 3.560e-003*sin(t)), 1.457e-001 +2.000*( 2.342e-001* 7.671e-003*cos(t)+ 9.722e-001* 3.560e-003*sin(t)) not\r
-# Age 90, p23 - p12\r
-set label "90" at 2.004e-001, 2.292e-001 center\r
-replot 2.004e-001+ 2.000*( 6.128e-001* 9.486e-003*cos(t)+-7.902e-001* 7.229e-003*sin(t)), 2.292e-001 +2.000*( 7.902e-001* 9.486e-003*cos(t)+ 6.128e-001* 7.229e-003*sin(t)) not\r
-# Age 95, p23 - p12\r
-set label "95" at 2.085e-001, 3.591e-001 center\r
-replot 2.085e-001+ 2.000*( 2.248e-001* 1.970e-002*cos(t)+-9.744e-001* 1.148e-002*sin(t)), 3.591e-001 +2.000*( 9.744e-001* 1.970e-002*cos(t)+ 2.248e-001* 1.148e-002*sin(t)) not\r
-set out "biaspar/varpijgrbiaspar123-12.png";replot;\r
-set parametric;unset label\r
-set log y;set log x; set xlabel "p21 (year-1)";set ylabel "p13 (year-1)"\r
-set ter png small\r
-set size 0.65,0.65\r
-set out "biaspar/varpijgrbiaspar121-13.png"\r
-set label "65" at 1.936e-001, 1.459e-002 center\r
-# Age 65, p21 - p13\r
-plot [-pi:pi] 1.936e-001+ 2.000*( 1.000e+000* 3.150e-002*cos(t)+-1.880e-003* 1.741e-003*sin(t)), 1.459e-002 +2.000*( 1.880e-003* 3.150e-002*cos(t)+ 1.000e+000* 1.741e-003*sin(t)) not\r
-# Age 70, p21 - p13\r
-set label "70" at 1.734e-001, 1.976e-002 center\r
-replot 1.734e-001+ 2.000*( 1.000e+000* 2.160e-002*cos(t)+-1.974e-003* 1.743e-003*sin(t)), 1.976e-002 +2.000*( 1.974e-003* 2.160e-002*cos(t)+ 1.000e+000* 1.743e-003*sin(t)) not\r
-# Age 75, p21 - p13\r
-set label "75" at 1.552e-001, 2.674e-002 center\r
-replot 1.552e-001+ 2.000*( 1.000e+000* 1.376e-002*cos(t)+-1.404e-003* 1.636e-003*sin(t)), 2.674e-002 +2.000*( 1.404e-003* 1.376e-002*cos(t)+ 1.000e+000* 1.636e-003*sin(t)) not\r
-# Age 80, p21 - p13\r
-set label "80" at 1.389e-001, 3.614e-002 center\r
-replot 1.389e-001+ 2.000*( 1.000e+000* 8.253e-003*cos(t)+-3.684e-003* 1.671e-003*sin(t)), 3.614e-002 +2.000*( 3.684e-003* 8.253e-003*cos(t)+ 1.000e+000* 1.671e-003*sin(t)) not\r
-# Age 85, p21 - p13\r
-set label "85" at 1.243e-001, 4.875e-002 center\r
-replot 1.243e-001+ 2.000*( 9.992e-001* 6.301e-003*cos(t)+-4.077e-002* 2.642e-003*sin(t)), 4.875e-002 +2.000*( 4.077e-002* 6.301e-003*cos(t)+ 9.992e-001* 2.642e-003*sin(t)) not\r
-# Age 90, p21 - p13\r
-set label "90" at 1.112e-001, 6.557e-002 center\r
-replot 1.112e-001+ 2.000*( 9.932e-001* 7.891e-003*cos(t)+-1.164e-001* 5.116e-003*sin(t)), 6.557e-002 +2.000*( 1.164e-001* 7.891e-003*cos(t)+ 9.932e-001* 5.116e-003*sin(t)) not\r
-# Age 95, p21 - p13\r
-set label "95" at 9.953e-002, 8.778e-002 center\r
-replot 9.953e-002+ 2.000*( 9.056e-001* 1.057e-002*cos(t)+-4.241e-001* 9.328e-003*sin(t)), 8.778e-002 +2.000*( 4.241e-001* 1.057e-002*cos(t)+ 9.056e-001* 9.328e-003*sin(t)) not\r
-set out "biaspar/varpijgrbiaspar121-13.png";replot;\r
-set parametric;unset label\r
-set log y;set log x; set xlabel "p23 (year-1)";set ylabel "p13 (year-1)"\r
-set ter png small\r
-set size 0.65,0.65\r
-set out "biaspar/varpijgrbiaspar123-13.png"\r
-set label "65" at 1.640e-001, 1.459e-002 center\r
-# Age 65, p23 - p13\r
-plot [-pi:pi] 1.640e-001+ 2.000*( 9.993e-001* 2.108e-002*cos(t)+ 3.790e-002* 1.549e-003*sin(t)), 1.459e-002 +2.000*(-3.790e-002* 2.108e-002*cos(t)+ 9.993e-001* 1.549e-003*sin(t)) not\r
-# Age 70, p23 - p13\r
-set label "70" at 1.708e-001, 1.976e-002 center\r
-replot 1.708e-001+ 2.000*( 9.988e-001* 1.745e-002*cos(t)+ 4.951e-002* 1.516e-003*sin(t)), 1.976e-002 +2.000*(-4.951e-002* 1.745e-002*cos(t)+ 9.988e-001* 1.516e-003*sin(t)) not\r
-# Age 75, p23 - p13\r
-set label "75" at 1.778e-001, 2.674e-002 center\r
-replot 1.778e-001+ 2.000*( 9.978e-001* 1.368e-002*cos(t)+ 6.667e-002* 1.362e-003*sin(t)), 2.674e-002 +2.000*(-6.667e-002* 1.368e-002*cos(t)+ 9.978e-001* 1.362e-003*sin(t)) not\r
-# Age 80, p23 - p13\r
-set label "80" at 1.851e-001, 3.614e-002 center\r
-replot 1.851e-001+ 2.000*( 9.950e-001* 1.006e-002*cos(t)+ 1.004e-001* 1.338e-003*sin(t)), 3.614e-002 +2.000*(-1.004e-001* 1.006e-002*cos(t)+ 9.950e-001* 1.338e-003*sin(t)) not\r
-# Age 85, p23 - p13\r
-set label "85" at 1.926e-001, 4.875e-002 center\r
-replot 1.926e-001+ 2.000*( 9.801e-001* 7.644e-003*cos(t)+ 1.985e-001* 2.219e-003*sin(t)), 4.875e-002 +2.000*(-1.985e-001* 7.644e-003*cos(t)+ 9.801e-001* 2.219e-003*sin(t)) not\r
-# Age 90, p23 - p13\r
-set label "90" at 2.004e-001, 6.557e-002 center\r
-replot 2.004e-001+ 2.000*( 9.273e-001* 8.612e-003*cos(t)+ 3.743e-001* 4.351e-003*sin(t)), 6.557e-002 +2.000*(-3.743e-001* 8.612e-003*cos(t)+ 9.273e-001* 4.351e-003*sin(t)) not\r
-# Age 95, p23 - p13\r
-set label "95" at 2.085e-001, 8.778e-002 center\r
-replot 2.085e-001+ 2.000*( 8.652e-001* 1.310e-002*cos(t)+ 5.014e-001* 8.033e-003*sin(t)), 8.778e-002 +2.000*(-5.014e-001* 1.310e-002*cos(t)+ 8.652e-001* 8.033e-003*sin(t)) not\r
-set out "biaspar/varpijgrbiaspar123-13.png";replot;\r
-set parametric;unset label\r
-set log y;set log x; set xlabel "p23 (year-1)";set ylabel "p21 (year-1)"\r
-set ter png small\r
-set size 0.65,0.65\r
-set out "biaspar/varpijgrbiaspar123-21.png"\r
-set label "65" at 1.640e-001, 1.936e-001 center\r
-# Age 65, p23 - p21\r
-plot [-pi:pi] 1.640e-001+ 2.000*( 3.032e-002* 3.151e-002*cos(t)+ 9.995e-001* 2.105e-002*sin(t)), 1.936e-001 +2.000*(-9.995e-001* 3.151e-002*cos(t)+ 3.032e-002* 2.105e-002*sin(t)) not\r
-# Age 70, p23 - p21\r
-set label "70" at 1.708e-001, 1.734e-001 center\r
-replot 1.708e-001+ 2.000*( 4.964e-002* 2.161e-002*cos(t)+ 9.988e-001* 1.741e-002*sin(t)), 1.734e-001 +2.000*(-9.988e-001* 2.161e-002*cos(t)+ 4.964e-002* 1.741e-002*sin(t)) not\r
-# Age 75, p23 - p21\r
-set label "75" at 1.778e-001, 1.552e-001 center\r
-replot 1.778e-001+ 2.000*( 5.539e-001* 1.385e-002*cos(t)+ 8.326e-001* 1.356e-002*sin(t)), 1.552e-001 +2.000*(-8.326e-001* 1.385e-002*cos(t)+ 5.539e-001* 1.356e-002*sin(t)) not\r
-# Age 80, p23 - p21\r
-set label "80" at 1.851e-001, 1.389e-001 center\r
-replot 1.851e-001+ 2.000*( 9.977e-001* 1.002e-002*cos(t)+ 6.827e-002* 8.244e-003*sin(t)), 1.389e-001 +2.000*(-6.827e-002* 1.002e-002*cos(t)+ 9.977e-001* 8.244e-003*sin(t)) not\r
-# Age 85, p23 - p21\r
-set label "85" at 1.926e-001, 1.243e-001 center\r
-replot 1.926e-001+ 2.000*( 9.865e-001* 7.536e-003*cos(t)+ 1.638e-001* 6.259e-003*sin(t)), 1.243e-001 +2.000*(-1.638e-001* 7.536e-003*cos(t)+ 9.865e-001* 6.259e-003*sin(t)) not\r
-# Age 90, p23 - p21\r
-set label "90" at 2.004e-001, 1.112e-001 center\r
-replot 2.004e-001+ 2.000*( 8.440e-001* 8.341e-003*cos(t)+ 5.363e-001* 7.658e-003*sin(t)), 1.112e-001 +2.000*(-5.363e-001* 8.341e-003*cos(t)+ 8.440e-001* 7.658e-003*sin(t)) not\r
-# Age 95, p23 - p21\r
-set label "95" at 2.085e-001, 9.953e-002 center\r
-replot 2.085e-001+ 2.000*( 9.795e-001* 1.210e-002*cos(t)+ 2.015e-001* 1.028e-002*sin(t)), 9.953e-002 +2.000*(-2.015e-001* 1.210e-002*cos(t)+ 9.795e-001* 1.028e-002*sin(t)) not\r
-set out "biaspar/varpijgrbiaspar123-21.png";replot;\r
-# Routine varevsij\r
-set noparametric;set nolabel; set ter png small;set size 0.65, 0.65\r
- set log y; set nolog x;set xlabel "Age"; set ylabel "Force of mortality (year-1)";\r
- plot "biaspar/prmorprev1-stablbased-rbiaspar.txt" u 1:($3) not w l 1 \r
- replot "biaspar/prmorprev1-stablbased-rbiaspar.txt" u 1:(($3+1.96*$4)) t "95% interval" w l 2 \r
- replot "biaspar/prmorprev1-stablbased-rbiaspar.txt" u 1:(($3-1.96*$4)) not w l 2 \r
-set out "biaspar/varmuptjgr-stablbased-biaspar1.png";replot;\r
+
+# Imach version 0.98, September 2005, INED-EUROREVES
+# biaspar.gp
+set missing 'NaNq'
+cd "/Users/brouard/bin/html/doc"
+
+set out "biaspar/vbiaspar11.png"
+
+#set out "vbiaspar11.png"
+set xlabel "Age"
+set ylabel "Probability"
+set ter png small
+set size 0.65,0.65
+plot [70:95] "biaspar/vplrbiaspar.txt" every :::0::0 u 1:2 "%lf %lf (%lf) %*lf (%*lf)" t"Stable prevalence" w l 0,"biaspar/vplrbiaspar.txt" every :::0::0 u 1:($2+1.96*$3) "%lf %lf (%lf) %*lf (%*lf)" t"95% CI" w l 1,"biaspar/vplrbiaspar.txt" every :::0::0 u 1:($2-1.96*$3) "%lf %lf (%lf) %*lf (%*lf)" t"" w l 1,"biaspar/prbiaspar.txt" every :::0::0 u 1:($2) t"Observed prevalence " w l 2
+set out "biaspar/vbiaspar21.png"
+
+#set out "vbiaspar21.png"
+set xlabel "Age"
+set ylabel "Probability"
+set ter png small
+set size 0.65,0.65
+plot [70:95] "biaspar/vplrbiaspar.txt" every :::0::0 u 1:2 "%lf %*lf (%*lf) %lf (%lf)" t"Stable prevalence" w l 0,"biaspar/vplrbiaspar.txt" every :::0::0 u 1:($2+1.96*$3) "%lf %*lf (%*lf) %lf (%lf)" t"95% CI" w l 1,"biaspar/vplrbiaspar.txt" every :::0::0 u 1:($2-1.96*$3) "%lf %*lf (%*lf) %lf (%lf)" t"" w l 1,"biaspar/prbiaspar.txt" every :::0::0 u 1:($6) t"Observed prevalence " w l 2
+set out "biaspar/ebiaspar1.png"
+set ylabel "Years"
+set ter png small
+set size 0.65,0.65
+plot [70:95] "biaspar/trbiaspar.txt" every :::0::0 u 1:2 "%lf %lf (%lf) %*lf (%*lf) %*lf (%*lf)" t"TLE" w l ,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2-$3*2) "%lf %lf (%lf) %*lf (%*lf) %*lf (%*lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2+$3*2) "%lf %lf (%lf) %*lf (%*lf) %*lf (%*lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:2 "%lf %*lf (%*lf) %lf (%lf) %*lf (%*lf)" t"LE in state (1)" w l ,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2-$3*2) "%lf %*lf (%*lf) %lf (%lf) %*lf (%*lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2+$3*2) "%lf %*lf (%*lf) %lf (%lf) %*lf (%*lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:2 "%lf %*lf (%*lf) %*lf (%*lf) %lf (%lf)" t"LE in state (2)" w l ,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2-$3*2) "%lf %*lf (%*lf) %*lf (%*lf) %lf (%lf)" t"" w l 0,"biaspar/trbiaspar.txt" every :::0::0 u 1:($2+$3*2) "%lf %*lf (%*lf) %*lf (%*lf) %lf (%lf)" t"" w l 0
+set out "biaspar/expbiaspar11.png"
+set ter png small
+set size 0.65,0.65
+plot [70:95] "biaspar/erbiaspar.txt" every :::0::0 u 1:2 t "e11" w l ,"biaspar/erbiaspar.txt" every :::0::0 u 1:4 t "e12" w l
+set out "biaspar/expbiaspar21.png"
+set ter png small
+set size 0.65,0.65
+plot [70:95] "biaspar/erbiaspar.txt" every :::0::0 u 1:6 t "e21" w l ,"biaspar/erbiaspar.txt" every :::0::0 u 1:8 t "e22" w l
+set out "biaspar/pbiaspar11.png"
+set xlabel "Age"
+set ylabel "Probability"
+set ter png small
+set size 0.65,0.65
+unset log y
+plot [70:95] "biaspar/pijrbiaspar.txt" u ($1==1 ? ($3):1/0):($5/($4+$5)) t"prev(1,2)" w l,"biaspar/pijrbiaspar.txt" u ($1==1 ? ($3):1/0):($8/($7+$8)) t"prev(2,2)" w l
+
+set out "biaspar/pbiaspar21.png"
+set xlabel "Age"
+set ylabel "Probability"
+set ter png small
+set size 0.65,0.65
+unset log y
+plot [70:95] "biaspar/pijrbiaspar.txt" u ($1==1 ? ($3):1/0):($6/($4+$5)) t"prev(2,3)" w l,"biaspar/pijrbiaspar.txt" u ($1==1 ? ($3):1/0):($12/($10+$11)) t"prev(3,3)" w l
+p1=-12.245504
+p2=0.092361
+p3=-10.670953
+p4=0.060958
+p5=-2.645034
+p6=-0.022329
+p7=-4.775501
+p8=0.007884
+
+set out "biaspar/pebiaspar11.png"
+
+set title "Probability"
+
+set ter png small
+set size 0.65,0.65
+set log y
+plot [70:95] exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)) t "p12" , exp(p3+p4*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)) t "p13" , exp(p5+p6*x)/(1+exp(p5+p6*x)+exp(p7+p8*x)) t "p21" , exp(p7+p8*x)/(1+exp(p5+p6*x)+exp(p7+p8*x)) t "p23"
+set out "biaspar/pebiaspar12.png"
+
+set ylabel "Quasi-incidence per year"
+
+set ter png small
+set size 0.65,0.65
+set log y
+plot [70:95] 12.000000*exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)) t "p12" , 12.000000*exp(p3+p4*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)) t "p13" , 12.000000*exp(p5+p6*x)/(1+exp(p5+p6*x)+exp(p7+p8*x)) t "p21" , 12.000000*exp(p7+p8*x)/(1+exp(p5+p6*x)+exp(p7+p8*x)) t "p23"
+# Routine varprob
+set parametric;unset label
+set log y;set log x; set xlabel "p13 (year-1)";set ylabel "p12 (year-1)"
+set ter png small
+set size 0.65,0.65
+set out "biaspar/varpijgrbiaspar113-12.png"
+set label "65" at 1.460e-02, 2.328e-02 center
+# Age 65, p13 - p12
+plot [-pi:pi] 1.460e-02+ 2.000*( 7.019e-01* 2.099e-03*cos(t)+ 7.123e-01* 1.386e-03*sin(t)), 2.328e-02 +2.000*( -7.123e-01* 2.099e-03*cos(t)+ 7.019e-01* 1.386e-03*sin(t)) not
+# Age 70, p13 - p12
+set label "70" at 1.977e-02, 3.688e-02 center
+replot 1.977e-02+ 2.000*( 5.418e-01* 2.359e-03*cos(t)+ 8.405e-01* 1.461e-03*sin(t)), 3.688e-02 +2.000*( -8.405e-01* 2.359e-03*cos(t)+ 5.418e-01* 1.461e-03*sin(t)) not
+# Age 75, p13 - p12
+set label "75" at 2.675e-02, 5.839e-02 center
+replot 2.675e-02+ 2.000*( 4.274e-01* 2.544e-03*cos(t)+ 9.041e-01* 1.383e-03*sin(t)), 5.839e-02 +2.000*( -9.041e-01* 2.544e-03*cos(t)+ 4.274e-01* 1.383e-03*sin(t)) not
+# Age 80, p13 - p12
+set label "80" at 3.615e-02, 9.232e-02 center
+replot 3.615e-02+ 2.000*( 3.992e-01* 2.744e-03*cos(t)+ 9.169e-01* 1.381e-03*sin(t)), 9.232e-02 +2.000*( -9.169e-01* 2.744e-03*cos(t)+ 3.992e-01* 1.381e-03*sin(t)) not
+# Age 85, p13 - p12
+set label "85" at 4.875e-02, 1.457e-01 center
+replot 4.875e-02+ 2.000*( 3.981e-01* 4.136e-03*cos(t)+ 9.174e-01* 2.268e-03*sin(t)), 1.457e-01 +2.000*( -9.174e-01* 4.136e-03*cos(t)+ 3.981e-01* 2.268e-03*sin(t)) not
+# Age 90, p13 - p12
+set label "90" at 6.556e-02, 2.292e-01 center
+replot 6.556e-02+ 2.000*( 2.987e-01* 9.027e-03*cos(t)+ 9.543e-01* 4.655e-03*sin(t)), 2.292e-01 +2.000*( -9.543e-01* 9.027e-03*cos(t)+ 2.987e-01* 4.655e-03*sin(t)) not
+# Age 95, p13 - p12
+set label "95" at 8.777e-02, 3.591e-01 center
+replot 8.777e-02+ 2.000*( 2.247e-01* 1.984e-02*cos(t)+ 9.744e-01* 8.795e-03*sin(t)), 3.591e-01 +2.000*( -9.744e-01* 1.984e-02*cos(t)+ 2.247e-01* 8.795e-03*sin(t)) not
+set out "biaspar/varpijgrbiaspar113-12.png";replot;
+set parametric;unset label
+set log y;set log x; set xlabel "p21 (year-1)";set ylabel "p12 (year-1)"
+set ter png small
+set size 0.65,0.65
+set out "biaspar/varpijgrbiaspar121-12.png"
+set label "65" at 1.936e-01, 2.328e-02 center
+# Age 65, p21 - p12
+plot [-pi:pi] 1.936e-01+ 2.000*( 9.998e-01* 3.109e-02*cos(t)+ -1.822e-02* 1.692e-03*sin(t)), 2.328e-02 +2.000*( 1.822e-02* 3.109e-02*cos(t)+ 9.998e-01* 1.692e-03*sin(t)) not
+# Age 70, p21 - p12
+set label "70" at 1.734e-01, 3.688e-02 center
+replot 1.734e-01+ 2.000*( 9.995e-01* 2.135e-02*cos(t)+ -3.169e-02* 2.026e-03*sin(t)), 3.688e-02 +2.000*( 3.169e-02* 2.135e-02*cos(t)+ 9.995e-01* 2.026e-03*sin(t)) not
+# Age 75, p21 - p12
+set label "75" at 1.552e-01, 5.839e-02 center
+replot 1.552e-01+ 2.000*( 9.985e-01* 1.365e-02*cos(t)+ -5.500e-02* 2.256e-03*sin(t)), 5.839e-02 +2.000*( 5.500e-02* 1.365e-02*cos(t)+ 9.985e-01* 2.256e-03*sin(t)) not
+# Age 80, p21 - p12
+set label "80" at 1.389e-01, 9.232e-02 center
+replot 1.389e-01+ 2.000*( 9.951e-01* 8.259e-03*cos(t)+ -9.930e-02* 2.453e-03*sin(t)), 9.232e-02 +2.000*( 9.930e-02* 8.259e-03*cos(t)+ 9.951e-01* 2.453e-03*sin(t)) not
+# Age 85, p21 - p12
+set label "85" at 1.243e-01, 1.457e-01 center
+replot 1.243e-01+ 2.000*( 9.672e-01* 6.435e-03*cos(t)+ -2.542e-01* 3.661e-03*sin(t)), 1.457e-01 +2.000*( 2.542e-01* 6.435e-03*cos(t)+ 9.672e-01* 3.661e-03*sin(t)) not
+# Age 90, p21 - p12
+set label "90" at 1.112e-01, 2.292e-01 center
+replot 1.112e-01+ 2.000*( 5.677e-01* 9.492e-03*cos(t)+ -8.232e-01* 6.841e-03*sin(t)), 2.292e-01 +2.000*( 8.232e-01* 9.492e-03*cos(t)+ 5.677e-01* 6.841e-03*sin(t)) not
+# Age 95, p21 - p12
+set label "95" at 9.952e-02, 3.591e-01 center
+replot 9.952e-02+ 2.000*( 2.083e-01* 1.976e-02*cos(t)+ -9.781e-01* 9.575e-03*sin(t)), 3.591e-01 +2.000*( 9.781e-01* 1.976e-02*cos(t)+ 2.083e-01* 9.575e-03*sin(t)) not
+set out "biaspar/varpijgrbiaspar121-12.png";replot;
+set parametric;unset label
+set log y;set log x; set xlabel "p23 (year-1)";set ylabel "p12 (year-1)"
+set ter png small
+set size 0.65,0.65
+set out "biaspar/varpijgrbiaspar123-12.png"
+set label "65" at 1.639e-01, 2.328e-02 center
+# Age 65, p23 - p12
+plot [-pi:pi] 1.639e-01+ 2.000*( 9.995e-01* 2.122e-02*cos(t)+ -3.216e-02* 1.649e-03*sin(t)), 2.328e-02 +2.000*( 3.216e-02* 2.122e-02*cos(t)+ 9.995e-01* 1.649e-03*sin(t)) not
+# Age 70, p23 - p12
+set label "70" at 1.707e-01, 3.688e-02 center
+replot 1.707e-01+ 2.000*( 9.988e-01* 1.755e-02*cos(t)+ -4.952e-02* 1.952e-03*sin(t)), 3.688e-02 +2.000*( 4.952e-02* 1.755e-02*cos(t)+ 9.988e-01* 1.952e-03*sin(t)) not
+# Age 75, p23 - p12
+set label "75" at 1.777e-01, 5.839e-02 center
+replot 1.777e-01+ 2.000*( 9.970e-01* 1.375e-02*cos(t)+ -7.687e-02* 2.132e-03*sin(t)), 5.839e-02 +2.000*( 7.687e-02* 1.375e-02*cos(t)+ 9.970e-01* 2.132e-03*sin(t)) not
+# Age 80, p23 - p12
+set label "80" at 1.850e-01, 9.232e-02 center
+replot 1.850e-01+ 2.000*( 9.925e-01* 1.011e-02*cos(t)+ -1.224e-01* 2.275e-03*sin(t)), 9.232e-02 +2.000*( 1.224e-01* 1.011e-02*cos(t)+ 9.925e-01* 2.275e-03*sin(t)) not
+# Age 85, p23 - p12
+set label "85" at 1.926e-01, 1.457e-01 center
+replot 1.926e-01+ 2.000*( 9.723e-01* 7.666e-03*cos(t)+ -2.339e-01* 3.562e-03*sin(t)), 1.457e-01 +2.000*( 2.339e-01* 7.666e-03*cos(t)+ 9.723e-01* 3.562e-03*sin(t)) not
+# Age 90, p23 - p12
+set label "90" at 2.004e-01, 2.292e-01 center
+replot 2.004e-01+ 2.000*( 6.167e-01* 9.540e-03*cos(t)+ -7.872e-01* 7.206e-03*sin(t)), 2.292e-01 +2.000*( 7.872e-01* 9.540e-03*cos(t)+ 6.167e-01* 7.206e-03*sin(t)) not
+# Age 95, p23 - p12
+set label "95" at 2.085e-01, 3.591e-01 center
+replot 2.085e-01+ 2.000*( 2.384e-01* 1.981e-02*cos(t)+ -9.712e-01* 1.149e-02*sin(t)), 3.591e-01 +2.000*( 9.712e-01* 1.981e-02*cos(t)+ 2.384e-01* 1.149e-02*sin(t)) not
+set out "biaspar/varpijgrbiaspar123-12.png";replot;
+set parametric;unset label
+set log y;set log x; set xlabel "p21 (year-1)";set ylabel "p13 (year-1)"
+set ter png small
+set size 0.65,0.65
+set out "biaspar/varpijgrbiaspar121-13.png"
+set label "65" at 1.936e-01, 1.460e-02 center
+# Age 65, p21 - p13
+plot [-pi:pi] 1.936e-01+ 2.000*( 1.000e+00* 3.109e-02*cos(t)+ -1.676e-03* 1.773e-03*sin(t)), 1.460e-02 +2.000*( 1.676e-03* 3.109e-02*cos(t)+ 1.000e+00* 1.773e-03*sin(t)) not
+# Age 70, p21 - p13
+set label "70" at 1.734e-01, 1.977e-02 center
+replot 1.734e-01+ 2.000*( 1.000e+00* 2.134e-02*cos(t)+ -1.717e-03* 1.772e-03*sin(t)), 1.977e-02 +2.000*( 1.717e-03* 2.134e-02*cos(t)+ 1.000e+00* 1.772e-03*sin(t)) not
+# Age 75, p21 - p13
+set label "75" at 1.552e-01, 2.675e-02 center
+replot 1.552e-01+ 2.000*( 1.000e+00* 1.363e-02*cos(t)+ -1.187e-03* 1.657e-03*sin(t)), 2.675e-02 +2.000*( 1.187e-03* 1.363e-02*cos(t)+ 1.000e+00* 1.657e-03*sin(t)) not
+# Age 80, p21 - p13
+set label "80" at 1.389e-01, 3.615e-02 center
+replot 1.389e-01+ 2.000*( 1.000e+00* 8.222e-03*cos(t)+ -3.844e-03* 1.674e-03*sin(t)), 3.615e-02 +2.000*( 3.844e-03* 8.222e-03*cos(t)+ 1.000e+00* 1.674e-03*sin(t)) not
+# Age 85, p21 - p13
+set label "85" at 1.243e-01, 4.875e-02 center
+replot 1.243e-01+ 2.000*( 9.992e-01* 6.297e-03*cos(t)+ -4.035e-02* 2.643e-03*sin(t)), 4.875e-02 +2.000*( 4.035e-02* 6.297e-03*cos(t)+ 9.992e-01* 2.643e-03*sin(t)) not
+# Age 90, p21 - p13
+set label "90" at 1.112e-01, 6.556e-02 center
+replot 1.112e-01+ 2.000*( 9.932e-01* 7.824e-03*cos(t)+ -1.163e-01* 5.151e-03*sin(t)), 6.556e-02 +2.000*( 1.163e-01* 7.824e-03*cos(t)+ 9.932e-01* 5.151e-03*sin(t)) not
+# Age 95, p21 - p13
+set label "95" at 9.952e-02, 8.777e-02 center
+replot 9.952e-02+ 2.000*( 8.754e-01* 1.047e-02*cos(t)+ -4.835e-01* 9.400e-03*sin(t)), 8.777e-02 +2.000*( 4.835e-01* 1.047e-02*cos(t)+ 8.754e-01* 9.400e-03*sin(t)) not
+set out "biaspar/varpijgrbiaspar121-13.png";replot;
+set parametric;unset label
+set log y;set log x; set xlabel "p23 (year-1)";set ylabel "p13 (year-1)"
+set ter png small
+set size 0.65,0.65
+set out "biaspar/varpijgrbiaspar123-13.png"
+set label "65" at 1.639e-01, 1.460e-02 center
+# Age 65, p23 - p13
+plot [-pi:pi] 1.639e-01+ 2.000*( 9.992e-01* 2.122e-02*cos(t)+ 3.972e-02* 1.562e-03*sin(t)), 1.460e-02 +2.000*( -3.972e-02* 2.122e-02*cos(t)+ 9.992e-01* 1.562e-03*sin(t)) not
+# Age 70, p23 - p13
+set label "70" at 1.707e-01, 1.977e-02 center
+replot 1.707e-01+ 2.000*( 9.987e-01* 1.756e-02*cos(t)+ 5.147e-02* 1.527e-03*sin(t)), 1.977e-02 +2.000*( -5.147e-02* 1.756e-02*cos(t)+ 9.987e-01* 1.527e-03*sin(t)) not
+# Age 75, p23 - p13
+set label "75" at 1.777e-01, 2.675e-02 center
+replot 1.777e-01+ 2.000*( 9.977e-01* 1.375e-02*cos(t)+ 6.833e-02* 1.368e-03*sin(t)), 2.675e-02 +2.000*( -6.833e-02* 1.375e-02*cos(t)+ 9.977e-01* 1.368e-03*sin(t)) not
+# Age 80, p23 - p13
+set label "80" at 1.850e-01, 3.615e-02 center
+replot 1.850e-01+ 2.000*( 9.949e-01* 1.009e-02*cos(t)+ 1.005e-01* 1.339e-03*sin(t)), 3.615e-02 +2.000*( -1.005e-01* 1.009e-02*cos(t)+ 9.949e-01* 1.339e-03*sin(t)) not
+# Age 85, p23 - p13
+set label "85" at 1.926e-01, 4.875e-02 center
+replot 1.926e-01+ 2.000*( 9.804e-01* 7.637e-03*cos(t)+ 1.972e-01* 2.228e-03*sin(t)), 4.875e-02 +2.000*( -1.972e-01* 7.637e-03*cos(t)+ 9.804e-01* 2.228e-03*sin(t)) not
+# Age 90, p23 - p13
+set label "90" at 2.004e-01, 6.556e-02 center
+replot 2.004e-01+ 2.000*( 9.254e-01* 8.649e-03*cos(t)+ 3.789e-01* 4.358e-03*sin(t)), 6.556e-02 +2.000*( -3.789e-01* 8.649e-03*cos(t)+ 9.254e-01* 4.358e-03*sin(t)) not
+# Age 95, p23 - p13
+set label "95" at 2.085e-01, 8.777e-02 center
+replot 2.085e-01+ 2.000*( 8.603e-01* 1.326e-02*cos(t)+ 5.098e-01* 8.022e-03*sin(t)), 8.777e-02 +2.000*( -5.098e-01* 1.326e-02*cos(t)+ 8.603e-01* 8.022e-03*sin(t)) not
+set out "biaspar/varpijgrbiaspar123-13.png";replot;
+set parametric;unset label
+set log y;set log x; set xlabel "p23 (year-1)";set ylabel "p21 (year-1)"
+set ter png small
+set size 0.65,0.65
+set out "biaspar/varpijgrbiaspar123-21.png"
+set label "65" at 1.639e-01, 1.936e-01 center
+# Age 65, p23 - p21
+plot [-pi:pi] 1.639e-01+ 2.000*( 3.376e-02* 3.110e-02*cos(t)+ 9.994e-01* 2.119e-02*sin(t)), 1.936e-01 +2.000*( -9.994e-01* 3.110e-02*cos(t)+ 3.376e-02* 2.119e-02*sin(t)) not
+# Age 70, p23 - p21
+set label "70" at 1.707e-01, 1.734e-01 center
+replot 1.707e-01+ 2.000*( 5.801e-02* 2.135e-02*cos(t)+ 9.983e-01* 1.752e-02*sin(t)), 1.734e-01 +2.000*( -9.983e-01* 2.135e-02*cos(t)+ 5.801e-02* 1.752e-02*sin(t)) not
+# Age 75, p23 - p21
+set label "75" at 1.777e-01, 1.552e-01 center
+replot 1.777e-01+ 2.000*( 8.046e-01* 1.382e-02*cos(t)+ 5.938e-01* 1.352e-02*sin(t)), 1.552e-01 +2.000*( -5.938e-01* 1.382e-02*cos(t)+ 8.046e-01* 1.352e-02*sin(t)) not
+# Age 80, p23 - p21
+set label "80" at 1.850e-01, 1.389e-01 center
+replot 1.850e-01+ 2.000*( 9.977e-01* 1.005e-02*cos(t)+ 6.821e-02* 8.213e-03*sin(t)), 1.389e-01 +2.000*( -6.821e-02* 1.005e-02*cos(t)+ 9.977e-01* 8.213e-03*sin(t)) not
+# Age 85, p23 - p21
+set label "85" at 1.926e-01, 1.243e-01 center
+replot 1.926e-01+ 2.000*( 9.869e-01* 7.531e-03*cos(t)+ 1.615e-01* 6.256e-03*sin(t)), 1.243e-01 +2.000*( -1.615e-01* 7.531e-03*cos(t)+ 9.869e-01* 6.256e-03*sin(t)) not
+# Age 90, p23 - p21
+set label "90" at 2.004e-01, 1.112e-01 center
+replot 2.004e-01+ 2.000*( 8.742e-01* 8.336e-03*cos(t)+ 4.856e-01* 7.619e-03*sin(t)), 1.112e-01 +2.000*( -4.856e-01* 8.336e-03*cos(t)+ 8.742e-01* 7.619e-03*sin(t)) not
+# Age 95, p23 - p21
+set label "95" at 2.085e-01, 9.952e-02 center
+replot 2.085e-01+ 2.000*( 9.838e-01* 1.218e-02*cos(t)+ 1.795e-01* 1.016e-02*sin(t)), 9.952e-02 +2.000*( -1.795e-01* 1.218e-02*cos(t)+ 9.838e-01* 1.016e-02*sin(t)) not
+set out "biaspar/varpijgrbiaspar123-21.png";replot;
+# Routine varevsij
+set noparametric;set nolabel; set ter png small;set size 0.65, 0.65
+ set log y; set nolog x;set xlabel "Age"; set ylabel "Force of mortality (year-1)";
+ plot "biaspar/prmorprev1-stablbased-rbiaspar.txt" u 1:($3) not w l 1
+ replot "biaspar/prmorprev1-stablbased-rbiaspar.txt" u 1:(($3+1.96*$4)) t "95% interval" w l 2
+ replot "biaspar/prmorprev1-stablbased-rbiaspar.txt" u 1:(($3-1.96*$4)) not w l 2
+set out "biaspar/varmuptjgr-stablbased-biaspar1.png";replot;
-<body>\r
-<title>IMaCh rbiaspar.txt</title>\r
- <font size="2">Imach version 0.07a, May 2004, INED-EUROREVES <br> $Revision$ $Date$</font> <hr size="2" color="#EC5E5E"> \r
-Title=1st_example <br>Datafile=data1.txt Firstpass=1 Lastpass=4 Stepm=1 Weight=0 Model=.<br>\r
-\r
-<hr size="2" color="#EC5E5E"> <ul><li><h4>Parameter files</h4>\r
- - Copy of the parameter file: <a href="orbiaspar.txt">orbiaspar.txt</a><br>\r
- - Log file of the run: <a href="biaspar.log">biaspar.log</a><br>\r
- - Gnuplot file name: <a href="biaspar.gp">biaspar.gp</a><br>\r
- - Date and time at start: Wed Jun 16 20:01:29 2004\r
-</ul>\r
-\r
-<br>Total number of observations=8270 <br>\r
-Youngest age at first (selected) pass 70.00, oldest age 104.17<br>\r
-Interval (in months) between two waves: Min=1 Max=74 Mean=24.04<br>\r
-\r
-<br>File of contributions to the likelihood: <a href="biaspar/ilkrbiaspar.txt">biaspar/ilkrbiaspar.txt</a><br>\r
-<ul><li><h4>Result files (first order: no variance)</h4>\r
- - Observed prevalence in each state (during the period defined between 1/1/1984 and 1/6/1988): <a href="biaspar/prbiaspar.txt">biaspar/prbiaspar.txt</a> <br>\r
- - Estimated transition probabilities over 1 (stepm) months: <a href="biaspar/pijrbiaspar.txt">biaspar/pijrbiaspar.txt</a><br>\r
- - Stable prevalence in each health state: <a href="biaspar/plrbiaspar.txt">biaspar/plrbiaspar.txt</a> <br>\r
- - Life expectancies by age and initial health status (estepm= 1 months): <a href="biaspar/erbiaspar.txt">biaspar/erbiaspar.txt</a> <br>\r
-</li> \r
-<ul><li><b>Graphs</b></li><p><br>- Pij or Conditional probabilities to be observed in state j being in state i, 1 (stepm) months before: biaspar/pebiaspar11.png<br> <img src="biaspar/pebiaspar11.png"><br>- Pij or Conditional probabilities to be observed in state j being in state i 1 (stepm) months before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too: biaspar/pebiaspar12.png<br> <img src="biaspar/pebiaspar12.png"><br>- Stable prevalence in each health state : pbiaspar/pbiaspar11.png<br> <img src="biaspar/pbiaspar11.png">\r
-<br>- Health life expectancies by age and initial health state (1): biaspar/expbiaspar11.png <br> <img src="biaspar/expbiaspar11.png">\r
-<br>- Health life expectancies by age and initial health state (2): biaspar/expbiaspar21.png <br> <img src="biaspar/expbiaspar21.png"></ul>\r
-<br><li><h4> Result files (second order: variances)</h4>\r
- - Parameter file with estimated parameters and covariance matrix: <a href="rbiaspar.imach">rbiaspar.imach</a> <br>\r
- - Variance of one-step probabilities: <a href="biaspar/probrbiaspar.txt">biaspar/probrbiaspar.txt</a> <br>\r
- - Variance-covariance of one-step probabilities: <a href="biaspar/probcovrbiaspar.txt">biaspar/probcovrbiaspar.txt</a> <br>\r
- - Correlation matrix of one-step probabilities: <a href="biaspar/probcorrbiaspar.txt">biaspar/probcorrbiaspar.txt</a> <br>\r
- - Variances and covariances of life expectancies by age and initial health status (estepm=1 months): <a href="biaspar/vrbiaspar.txt">biaspar/vrbiaspar.txt</a><br>\r
- - Health expectancies with their variances (no covariance): <a href="biaspar/trbiaspar.txt">biaspar/trbiaspar.txt</a> <br>\r
- - Standard deviation of stable prevalences: <a href="biaspar/vplrbiaspar.txt">biaspar/vplrbiaspar.txt</a> <br>\r
- <ul><li><b>Graphs</b></li><p><br>- Observed (cross-sectional) and period (incidence based) prevalence (with 95% confidence interval) in state (1): biaspar/vbiaspar11.png <br><img src="biaspar/vbiaspar11.png"><br>- Observed (cross-sectional) and period (incidence based) prevalence (with 95% confidence interval) in state (2): biaspar/vbiaspar21.png <br><img src="biaspar/vbiaspar21.png">\r
-<br>- Total life expectancy by age and health expectancies in states (1) and (2): biaspar/ebiaspar1.png<br><img src="biaspar/ebiaspar1.png"></ul>\r
-<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\r
-\r
-\r
-<li><h4> <a href="biaspar-cov.htm">Matrix of variance-covariance of pairs of step probabilities (drawings)</a></h4></li>\r
-\r
-<li><h4> Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)</h4></li>\r
-\r
-<br>-stablbased- <br>\r
-\r
-<br> File (multiple files are possible if covariates are present): <A href="biaspar/prmorprev1-stablbased-rbiaspar.txt">biaspar/prmorprev1-stablbased-rbiaspar.txt</a>\r
-\r
-<br> Probability is computed over estepm=1 months. <br> <img src="biaspar/varmuptjgr-stablbased-biaspar1.png"> <br>\r
-<br>Local time at start Wed Jun 16 20:01:29 2004\r
-<br>Local time at end Wed Jun 16 21:55:16 2004\r
+<body>
+<title>IMaCh rbiaspar.txt</title>
+ <font size="2">Imach version 0.98, September 2005, INED-EUROREVES <br> $Revision$ $Date$</font> <hr size="2" color="#EC5E5E">
+Title=1st_example <br>Datafile=data1.txt Firstpass=1 Lastpass=4 Stepm=1 Weight=0 Model=.<br>
+
+<hr size="2" color="#EC5E5E"> <ul><li><h4>Parameter files</h4>
+ - Copy of the parameter file: <a href="orbiaspar.txt">orbiaspar.txt</a><br>
+ - Log file of the run: <a href="biaspar.log">biaspar.log</a><br>
+ - Gnuplot file name: <a href="biaspar.gp">biaspar.gp</a><br>
+ - Date and time at start: Mon Oct 24 14:51:36 2005
+</ul>
+
+<br>Total number of observations=8270 <br>
+Youngest age at first (selected) pass 70.00, oldest age 104.17<br>
+Interval (in months) between two waves: Min=1 Max=74 Mean=24.04<br>
+
+<br>File of contributions to the likelihood: <a href="biaspar/ilkrbiaspar.txt">biaspar/ilkrbiaspar.txt</a><br>
+<ul><li><h4>Result files (first order: no variance)</h4>
+ - Observed prevalence in each state (during the period defined between 1/1/1984 and 1/6/1988): <a href="biaspar/prbiaspar.txt">biaspar/prbiaspar.txt</a> <br>
+ - Estimated transition probabilities over 1 (stepm) months: <a href="biaspar/pijrbiaspar.txt">biaspar/pijrbiaspar.txt</a><br>
+ - Stable prevalence in each health state: <a href="biaspar/plrbiaspar.txt">biaspar/plrbiaspar.txt</a> <br>
+ - Life expectancies by age and initial health status (estepm= 1 months): <a href="biaspar/erbiaspar.txt">biaspar/erbiaspar.txt</a> <br>
+</li>
+<ul><li><b>Graphs</b></li><p><br>- Pij or Conditional probabilities to be observed in state j being in state i, 1 (stepm) months before: biaspar/pebiaspar11.png<br> <img src="biaspar/pebiaspar11.png"><br>- Pij or Conditional probabilities to be observed in state j being in state i 1 (stepm) months before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too: biaspar/pebiaspar12.png<br> <img src="biaspar/pebiaspar12.png"><br>- Stable prevalence in each health state : pbiaspar/pbiaspar11.png<br> <img src="biaspar/pbiaspar11.png">
+<br>- Health life expectancies by age and initial health state (1): biaspar/expbiaspar11.png <br> <img src="biaspar/expbiaspar11.png">
+<br>- Health life expectancies by age and initial health state (2): biaspar/expbiaspar21.png <br> <img src="biaspar/expbiaspar21.png"></ul>
+<br><li><h4> Result files (second order: variances)</h4>
+ - Parameter file with estimated parameters and covariance matrix: <a href="rbiaspar.imach">rbiaspar.imach</a> <br>
+ - Variance of one-step probabilities: <a href="biaspar/probrbiaspar.txt">biaspar/probrbiaspar.txt</a> <br>
+ - Variance-covariance of one-step probabilities: <a href="biaspar/probcovrbiaspar.txt">biaspar/probcovrbiaspar.txt</a> <br>
+ - Correlation matrix of one-step probabilities: <a href="biaspar/probcorrbiaspar.txt">biaspar/probcorrbiaspar.txt</a> <br>
+ - Variances and covariances of life expectancies by age and initial health status (estepm=1 months): <a href="biaspar/vrbiaspar.txt">biaspar/vrbiaspar.txt</a><br>
+ - Health expectancies with their variances (no covariance): <a href="biaspar/trbiaspar.txt">biaspar/trbiaspar.txt</a> <br>
+ - Standard deviation of stable prevalences: <a href="biaspar/vplrbiaspar.txt">biaspar/vplrbiaspar.txt</a> <br>
+ <ul><li><b>Graphs</b></li><p><br>- Observed (cross-sectional) and period (incidence based) prevalence (with 95% confidence interval) in state (1): biaspar/vbiaspar11.png <br><img src="biaspar/vbiaspar11.png"><br>- Observed (cross-sectional) and period (incidence based) prevalence (with 95% confidence interval) in state (2): biaspar/vbiaspar21.png <br><img src="biaspar/vbiaspar21.png">
+<br>- Total life expectancy by age and health expectancies in states (1) and (2): biaspar/ebiaspar1.png<br><img src="biaspar/ebiaspar1.png"></ul>
+<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>
+
+
+<li><h4> <a href="biaspar-cov.htm">Matrix of variance-covariance of pairs of step probabilities (drawings)</a></h4></li>
+
+<li><h4> Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)</h4></li>
+
+<br>-stablbased- <br>
+
+<br> File (multiple files are possible if covariates are present): <A href="biaspar/prmorprev1-stablbased-rbiaspar.txt">biaspar/prmorprev1-stablbased-rbiaspar.txt</a>
+
+<br> Probability is computed over estepm=1 months. <br> <img src="biaspar/varmuptjgr-stablbased-biaspar1.png"> <br>
+<br>Local time at start Mon Oct 24 14:51:36 2005
+<br>Local time at end Mon Oct 24 16:19:18 2005
<br>
\ No newline at end of file
-Log filename:biaspar.log\r
-\r
-Imach version 0.07a, May 2004, INED-EUROREVES \r
-$Revision$ $Date$\r
-Enter the parameter file name: \r
-pathimach=C:\Program Files\IMaCh\bin\\r
-pathtot=D:\imachcvs\imach\html\doc\biaspar.imach\r
- path=D:\imachcvs\imach\html\doc\ \r
- optionfile=biaspar.imach\r
- optionfilext=imach\r
- optionfilefiname=biaspar\r
-Local time (at start): Wed Jun 16 20:01:29 2004\r
+Log filename:biaspar.log
+
+Imach version 0.98, September 2005, INED-EUROREVES
+$Revision$ $Date$
+Enter the parameter file name:
+pathimach=../../bin/
+pathtot=biaspar.imach
+ path=/Users/brouard/bin/html/doc
+ optionfile=biaspar.imach
+ optionfilext=imach
+ optionfilefiname=biaspar
+Local time (at start): Mon Oct 24 14:51:36 2005
# Imach version 0.97b, June 2004, INED-EUROREVES \r
-title=1st_example datafile=data1.txt lastobs=8600 firstpass=1 lastpass=4\r
-ftol=1.000000e-008 stepm=1 ncovcol=2 nlstate=2 ndeath=1 maxwav=4 mle=1 weight=0\r
-model=.\r
+title=1st_example datafile=data1.txt lastobs=8600 firstpass=1 lastpass=4
+ftol=1.000000e-08 stepm=1 ncovcol=2 nlstate=2 ndeath=1 maxwav=4 mle=1 weight=0
+model=.
# Parameters\r
-11 0.000000 0.000000\r
-12 0.000000 0.000000\r
-21 0.000000 0.000000\r
-22 0.000000 0.000000\r
+11 0.000000 0.000000
+12 0.000000 0.000000
+21 0.000000 0.000000
+22 0.000000 0.000000
# Scales\r
-12 0.000000e+000 0.000000e+000\r
-13 0.000000e+000 0.000000e+000\r
-21 0.000000e+000 0.000000e+000\r
-23 0.000000e+000 0.000000e+000\r
+12 0.000000e+00 0.000000e+00
+13 0.000000e+00 0.000000e+00
+21 0.000000e+00 0.000000e+00
+23 0.000000e+00 0.000000e+00
#covariance matrix#\r
-121 0.00000e+000\r
-122 0.00000e+000 0.00000e+000\r
-131 0.00000e+000 0.00000e+000 0.00000e+000\r
-132 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
-211 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
-212 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
-231 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
-232 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
-\r
-Total number of individuals= 8270, Agemin = 70.00, Agemax= 104.17\r
-\r
-Delay (in months) between two waves Min=1 Max=74 Mean=24.040080\r
-\r
- Age 70 1.=665 loss[1]=5.1% 2.=0 loss[2]=NaNQ% 1.=631 prev[1]=100.0% 2.=0 prev[2]=0.0% 1-1=34 11=563 12=33 13=35 33=6\r
-Age 71 1.=663 loss[1]=5.7% 2.=2 loss[2]=0.0% 1.=625 prev[1]=99.7% 2.=2 prev[2]=0.3% 1-1=38 11=530 12=47 13=48 21=1 22=1 3-1=2 33=31\r
-Age 72 1.=1181 loss[1]=5.6% 2.=35 loss[2]=5.7% 1.=1115 prev[1]=97.1% 2.=33 prev[2]=2.9% 1-1=66 11=969 12=70 13=76 2-1=2 21=9 22=18 23=6 3-1=2 33=87\r
-Age 73 1.=1119 loss[1]=5.1% 2.=48 loss[2]=8.3% 1.=1062 prev[1]=96.0% 2.=44 prev[2]=4.0% 1-1=57 11=912 12=71 13=79 2-1=4 21=12 22=26 23=6 3-1=12 33=94\r
-Age 74 1.=1563 loss[1]=4.2% 2.=90 loss[2]=4.4% 1.=1497 prev[1]=94.6% 2.=86 prev[2]=5.4% 1-1=66 11=1277 12=104 13=116 2-1=4 21=30 22=41 23=15 3-1=4 33=125\r
-Age 75 1.=1463 loss[1]=6.2% 2.=98 loss[2]=7.1% 1.=1372 prev[1]=93.8% 2.=91 prev[2]=6.2% 1-1=91 11=1155 12=98 13=119 2-1=7 21=15 22=55 23=21 3-1=4 33=124\r
-Age 76 1.=1390 loss[1]=4.5% 2.=112 loss[2]=3.6% 1.=1328 prev[1]=92.5% 2.=108 prev[2]=7.5% 1-1=62 11=1090 12=111 13=127 2-1=4 21=25 22=54 23=29 3-1=4 33=142\r
-Age 77 1.=1271 loss[1]=5.0% 2.=101 loss[2]=5.9% 1.=1208 prev[1]=92.7% 2.=95 prev[2]=7.3% 1-1=63 11=962 12=131 13=115 2-1=6 21=24 22=52 23=19 3-1=7 33=145\r
-Age 78 1.=1166 loss[1]=4.9% 2.=122 loss[2]=4.1% 1.=1109 prev[1]=90.5% 2.=117 prev[2]=9.5% 1-1=57 11=894 12=111 13=104 2-1=5 21=21 22=75 23=21 3-1=4 33=146\r
-Age 79 1.=1045 loss[1]=5.7% 2.=133 loss[2]=5.3% 1.=985 prev[1]=88.7% 2.=126 prev[2]=11.3% 1-1=60 11=773 12=109 13=103 2-1=7 21=31 22=68 23=27 3-1=8 33=136\r
-Age 80 1.=986 loss[1]=4.1% 2.=128 loss[2]=3.1% 1.=946 prev[1]=88.4% 2.=124 prev[2]=11.6% 1-1=40 11=718 12=140 13=88 2-1=4 21=21 22=71 23=32 3-1=6 33=121\r
-Age 81 1.=872 loss[1]=4.9% 2.=130 loss[2]=3.8% 1.=829 prev[1]=86.9% 2.=125 prev[2]=13.1% 1-1=43 11=629 12=102 13=98 2-1=5 21=24 22=74 23=27 3-1=5 33=126\r
-Age 82 1.=803 loss[1]=4.4% 2.=146 loss[2]=4.1% 1.=768 prev[1]=84.6% 2.=140 prev[2]=15.4% 1-1=35 11=546 12=131 13=91 2-1=6 21=15 22=77 23=48 3-1=11 33=100\r
-Age 83 1.=726 loss[1]=6.5% 2.=116 loss[2]=0.9% 1.=679 prev[1]=85.5% 2.=115 prev[2]=14.5% 1-1=47 11=456 12=124 13=99 2-1=1 21=19 22=71 23=25 3-1=8 33=133\r
-Age 84 1.=622 loss[1]=5.6% 2.=147 loss[2]=4.1% 1.=587 prev[1]=80.6% 2.=141 prev[2]=19.4% 1-1=35 11=394 12=112 13=81 2-1=6 21=18 22=82 23=41 3-1=5 33=114\r
-Age 85 1.=526 loss[1]=4.4% 2.=127 loss[2]=6.3% 1.=503 prev[1]=80.9% 2.=119 prev[2]=19.1% 1-1=23 11=315 12=122 13=66 2-1=8 21=13 22=67 23=39 3-1=4 33=137\r
-Age 86 1.=464 loss[1]=5.2% 2.=130 loss[2]=6.2% 1.=440 prev[1]=78.3% 2.=122 prev[2]=21.7% 1-1=24 11=271 12=103 13=66 2-1=8 21=18 22=70 23=34 3-1=3 33=112\r
-Age 87 1.=372 loss[1]=4.8% 2.=143 loss[2]=2.8% 1.=354 prev[1]=71.8% 2.=139 prev[2]=28.2% 1-1=18 11=219 12=79 13=56 2-1=4 21=15 22=71 23=53 3-1=1 33=81\r
-Age 88 1.=283 loss[1]=3.9% 2.=164 loss[2]=6.7% 1.=272 prev[1]=64.0% 2.=153 prev[2]=36.0% 1-1=11 11=172 12=63 13=37 2-1=11 21=25 22=84 23=44 3-1=8 33=102\r
-Age 89 1.=227 loss[1]=3.5% 2.=152 loss[2]=4.6% 1.=219 prev[1]=60.2% 2.=145 prev[2]=39.8% 1-1=8 11=135 12=45 13=39 2-1=7 21=21 22=73 23=51 3-1=2 33=77\r
-Age 90 1.=181 loss[1]=3.9% 2.=143 loss[2]=4.9% 1.=174 prev[1]=56.1% 2.=136 prev[2]=43.9% 1-1=7 11=104 12=41 13=29 2-1=7 21=18 22=82 23=36 3-1=1 33=75\r
-Age 91 1.=146 loss[1]=4.1% 2.=109 loss[2]=8.3% 1.=140 prev[1]=58.3% 2.=100 prev[2]=41.7% 1-1=6 11=78 12=36 13=26 2-1=9 21=11 22=51 23=38 3-1=3 33=77\r
-Age 92 1.=114 loss[1]=6.1% 2.=101 loss[2]=2.0% 1.=107 prev[1]=51.9% 2.=99 prev[2]=48.1% 1-1=7 11=47 12=43 13=17 2-1=2 21=11 22=52 23=36 3-1=2 33=61\r
-Age 93 1.=78 loss[1]=3.8% 2.=89 loss[2]=12.4% 1.=75 prev[1]=49.0% 2.=78 prev[2]=51.0% 1-1=3 11=36 12=25 13=14 2-1=11 21=10 22=46 23=22 3-1=2 33=62\r
-Age 94 1.=51 loss[1]=3.9% 2.=71 loss[2]=1.4% 1.=49 prev[1]=41.2% 2.=70 prev[2]=58.8% 1-1=2 11=24 12=8 13=17 2-1=1 21=4 22=39 23=27 3-1=1 33=37\r
-Age 95 1.=38 loss[1]=5.3% 2.=57 loss[2]=5.3% 1.=36 prev[1]=40.0% 2.=54 prev[2]=60.0% 1-1=2 11=16 12=13 13=7 2-1=3 21=4 22=31 23=19 3-1=1 33=39\r
-Age 96 1.=25 loss[1]=4.0% 2.=43 loss[2]=4.7% 1.=24 prev[1]=36.9% 2.=41 prev[2]=63.1% 1-1=1 11=11 12=9 13=4 2-1=2 21=2 22=22 23=17 3-1=2 33=25\r
-Age 97 1.=11 loss[1]=0.0% 2.=36 loss[2]=8.3% 1.=11 prev[1]=25.0% 2.=33 prev[2]=75.0% 11=4 12=7 2-1=3 21=2 22=22 23=9 33=23\r
-Age 98 1.=5 loss[1]=0.0% 2.=21 loss[2]=0.0% 1.=5 prev[1]=19.2% 2.=21 prev[2]=80.8% 11=1 12=4 21=1 22=13 23=7 3-1=1 33=17\r
-Age 99 1.=6 loss[1]=0.0% 2.=14 loss[2]=0.0% 1.=6 prev[1]=30.0% 2.=14 prev[2]=70.0% 11=3 12=1 13=2 21=2 22=2 23=10 33=6\r
-Age 100 1.=2 loss[1]=0.0% 2.=9 loss[2]=0.0% 1.=2 prev[1]=18.2% 2.=9 prev[2]=81.8% 11=1 12=1 21=2 22=5 23=2 33=2\r
-Age 101 1.=2 loss[1]=50.0% 2.=0 loss[2]=NaNQ% 1.=1 prev[1]=100.0% 2.=0 prev[2]=0.0% 1-1=1 12=1 3-1=1 33=3\r
-Age 102 1.=2 loss[1]=0.0% 2.=1 loss[2]=0.0% 1.=2 prev[1]=66.7% 2.=1 prev[2]=33.3% 12=2 22=1 33=1\r
-Age 103 1.=0 loss[1]=NaNQ% 2.=0 loss[2]=NaNQ% 1.=0 prev[1]=NaNQ% 2.=0 prev[2]=NaNQ%\r
-Age 104 1.=0 loss[1]=NaNQ% 2.=0 loss[2]=NaNQ% 1.=0 prev[1]=NaNQ% 2.=0 prev[2]=NaNQ%\r
-Age 105 1.=0 loss[1]=NaNQ% 2.=0 loss[2]=NaNQ% 1.=0 prev[1]=NaNQ% 2.=0 prev[2]=NaNQ%\r
-Age 106 1.=0 loss[1]=NaNQ% 2.=0 loss[2]=NaNQ% 1.=0 prev[1]=NaNQ% 2.=0 prev[2]=NaNQ% -1-1=69 -11=718 -12=195 -13=261\r
-Total 1.=18068 loss[1]=5.0% 2.=2818 loss[2]=4.9% 1.=17161 prev[1]=86.5% 2.=2681 prev[2]=13.5% -1-1=69 -11=718 -12=195 -13=261 1-1=907 11=13305 12=2097 13=1759 2-1=137 21=424 22=1496 23=761 3-1=114 33=2567\r
-Powell\r
- 1 0.000000000000 2 0.000000000000 3 0.000000000000 4 0.000000000000 5 0.000000000000 6 0.000000000000 7 0.000000000000 8 0.000000000000\r
-\r
-Considering the time needed for this last iteration #1: 6 seconds,\r
- - if your program needs 10 iterations to converge, convergence will be \r
- reached in 0 day(s) 0 hour(s) 0 minute(s) 54 second(s) or\r
- on Wed Jun 16 20:02:29 2004 (current time is Sun Jan 00 00:00:00 1900);\r
- - if your program needs 20 iterations to converge, convergence will be \r
- reached in 0 day(s) 0 hour(s) 1 minute(s) 54 second(s) or\r
- on Wed Jun 16 20:03:29 2004 (current time is Sun Jan 00 00:00:00 1900);\r
- - if your program needs 30 iterations to converge, convergence will be \r
- reached in 0 day(s) 0 hour(s) 2 minute(s) 54 second(s) or\r
- on Wed Jun 16 20:04:29 2004 (current time is Sun Jan 00 00:00:00 1900);\r
-1........2..............3.........4.....................5.....6............7.........8.............................. 1 8.981830476053 2 0.016741782348 3 -0.434998430400 4 0.000507430858 5 3.199437393212 6 -0.000133684761 7 -0.817356129028 8 0.000414699996\r
-\r
-Considering the time needed for this last iteration #2: 208 seconds,\r
- - if your program needs 10 iterations to converge, convergence will be \r
- reached in 0 day(s) 0 hour(s) 27 minute(s) 44 second(s) or\r
- on Wed Jun 16 20:32:47 2004 (current time is Wed Jun 16 20:04:29 2004);\r
- - if your program needs 20 iterations to converge, convergence will be \r
- reached in 0 day(s) 1 hour(s) 2 minute(s) 24 second(s) or\r
- on Wed Jun 16 21:07:27 2004 (current time is Wed Jun 16 20:04:29 2004);\r
- - if your program needs 30 iterations to converge, convergence will be \r
- reached in 0 day(s) 1 hour(s) 37 minute(s) 4 second(s) or\r
- on Wed Jun 16 21:42:07 2004 (current time is Wed Jun 16 20:04:29 2004);\r
-1...........2.....................3..........4..................5.................6................7..........8................. 1 -2.281836000719 2 0.011363386191 3 -3.509411216627 4 -0.009366673262 5 2.547958086578 6 -0.006889845670 7 -1.246132813756 8 -0.012649901977\r
-\r
-Considering the time needed for this last iteration #3: 231 seconds,\r
- - if your program needs 10 iterations to converge, convergence will be \r
- reached in 0 day(s) 0 hour(s) 26 minute(s) 57 second(s) or\r
- on Wed Jun 16 20:35:51 2004 (current time is Wed Jun 16 21:42:07 2004);\r
- - if your program needs 20 iterations to converge, convergence will be \r
- reached in 0 day(s) 1 hour(s) 5 minute(s) 27 second(s) or\r
- on Wed Jun 16 21:14:21 2004 (current time is Wed Jun 16 21:42:07 2004);\r
- - if your program needs 30 iterations to converge, convergence will be \r
- reached in 0 day(s) 1 hour(s) 43 minute(s) 57 second(s) or\r
- on Wed Jun 16 21:52:51 2004 (current time is Wed Jun 16 21:42:07 2004);\r
-1........2.................3......4....................5........6....................7..........8........... 1 -2.182035173603 2 0.011466563261 3 -4.731956899645 4 -0.008153719587 5 2.446929750692 6 -0.008350758063 7 -1.338373684045 8 -0.012700510705\r
-1........2................3..........4...................5.........6...................7..........8....................... 1 -3.070118367810 2 0.018029737925 3 -6.179758278003 4 0.001931815043 5 2.212099294068 6 -0.027639659092 7 -2.308826366165 8 -0.013145859018\r
-1........2...............3..........4....................5........6..........7..........8........... 1 -3.626443405216 2 0.020252747011 3 -6.684567970636 4 0.006053308971 5 2.123889813050 6 -0.032646572927 7 -2.451161675313 8 -0.013247292052\r
-1.........2................3..........4....................5........6..........7..........8................ 1 -7.192140554152 2 0.034622189094 3 -10.544920216832 4 0.036670473931 5 1.542086623550 6 -0.063020682713 7 -2.948009202319 8 -0.013799972401\r
-1.........2...........3.........4...................5.........6............7..........8......... 1 -7.695063925884 2 0.037191994983 3 -9.231166162442 4 0.039361834929 5 1.401759549812 6 -0.065175804333 7 -2.866441706489 8 -0.013803517142\r
-1.........2.............3..........4...................5.........6...........7...........8......... 1 -7.939869836890 2 0.039878300993 3 -9.189584027736 4 0.041402834643 5 1.337329427407 6 -0.067669137298 7 -2.901398966684 8 -0.013846392284\r
-1.........2...............3...........4...................5.........6...........7...........8.................. 1 -8.176148664406 2 0.042830030891 3 -9.304682693761 4 0.043725020801 5 1.277039671360 6 -0.070125957584 7 -2.891194329467 8 -0.013891340738\r
-1.........2.........3..........4...................5..........6...........7..........8........ 1 -8.179619196119 2 0.042985027260 3 -9.366623520734 4 0.044108767751 5 1.279285841696 6 -0.070237071696 7 -2.878991733486 8 -0.013897703834\r
-1..........2.........3..........4...................5..........6...........7..........8................ 1 -8.254215888987 2 0.044554630734 3 -9.868950570120 4 0.048211083803 5 1.293769939843 6 -0.070742638143 7 -2.797695070311 8 -0.013959640477\r
-1..........2.........3........4....................5..........6...........7.........8........ 1 -8.301005986669 2 0.045044501039 3 -10.022401257526 4 0.050128392815 5 1.294592923683 6 -0.070705262279 7 -2.801675945921 8 -0.013983808787\r
-1..........2.........3........4....................5..........6...........7.........8................ 1 -9.365674779567 2 0.057619122398 3 -13.303145173616 4 0.092884999270 5 1.298783095758 6 -0.069466271843 7 -2.845791465313 8 -0.014517443646\r
-1.........2.........3........4...................5..........6...........7........8......... 1 -9.460316475357 2 0.058991649124 3 -13.724001592567 4 0.097155016842 5 1.308864005060 6 -0.069456560690 7 -2.836197284189 8 -0.014578614460\r
-1..........2.........3........4...................5..........6...........7.........8.......... 1 -9.557567205936 2 0.060205222047 3 -13.943564483557 4 0.099318409496 5 1.302759025124 6 -0.069576980550 7 -2.798221359597 8 -0.014606145260\r
-1.....................2.........3........4...................5...........6...................7.........8....... 1 -9.571680690088 2 0.060355413693 3 -13.930383304540 4 0.099316840292 5 1.298874982881 6 -0.069462813075 7 -2.794978077764 8 -0.014604991425\r
-1.........2.........3........4...................5..............6............7.........8............. 1 -9.521361381226 2 0.059769030435 3 -13.376711224686 4 0.092703049694 5 1.274511227165 6 -0.068992405398 7 -2.776810027970 8 -0.014526321197\r
-1.........2.........3........4...................5..........6...........7........8....... 1 -9.561610650197 2 0.060333064678 3 -13.311561847194 4 0.091813448248 5 1.264184698318 6 -0.068851771915 7 -2.776201360099 8 -0.014524503040\r
-1.........2.........3........4...................5..........6..........7........8............... 1 -11.211324000532 2 0.080499481387 3 -11.534523184767 4 0.070951238492 5 0.868294913853 6 -0.064116781761 7 -2.823405150705 8 -0.014536596737\r
-1.........2.........3........4...................5..............6...........7........8........ 1 -11.325310955194 2 0.081616513818 3 -11.380980714273 4 0.068831965017 5 0.838804004101 6 -0.063946246576 7 -2.827156746942 8 -0.014528250125\r
-1.........2.........3........4....................5..........6...........7................8........... 1 -11.341383332565 2 0.081799321174 3 -11.416642934906 4 0.069267171229 5 0.838213512157 6 -0.063887081804 7 -2.826532965018 8 -0.014533217276\r
-1...................2..............3...........4....................5..........6....................7.........8................... 1 -11.341251180867 2 0.081809169639 3 -11.417519238440 4 0.069282438001 5 0.837970168424 6 -0.063846744439 7 -2.824855670714 8 -0.014529898929\r
-1.........2.........3...........4.......................5.............6..........7.........8....... 1 -11.343266349117 2 0.081826536932 3 -11.402053359447 4 0.069094032402 5 0.836444724102 6 -0.063829057413 7 -2.824951916980 8 -0.014526594646\r
-1...................2............3.........4......................5............6.............7........8............ 1 -11.343831993268 2 0.081795493001 3 -11.290080377801 4 0.067708454220 5 0.823149667183 6 -0.063668261224 7 -2.828143430305 8 -0.014467790128\r
-1..........2...........3........4...................5..........6........7............8............ 1 -11.346751409083 2 0.081796777704 3 -11.192371885181 4 0.066502288381 5 0.801418624881 6 -0.063410285815 7 -2.836818340196 8 -0.014350793327\r
-1.........2.........3........4...................5..........6........7...............8............ 1 -11.375014786746 2 0.082022174368 3 -10.818445447108 4 0.061912610253 5 0.651625897249 6 -0.061563815283 7 -2.904793363312 8 -0.013469599464\r
-1.........2.........3........4...................5..........6........7..........8............. 1 -11.499043733155 2 0.083397251873 3 -10.221945018250 4 0.054692794514 5 0.107569323894 6 -0.054805981466 7 -3.176375920307 8 -0.010082569530\r
-1.........2.........3........4...................5..........6........7........8............... 1 -11.844397469756 2 0.087626315750 3 -9.770871849589 4 0.049494625340 5 -1.251671942221 6 -0.038145984122 7 -3.899459022947 8 -0.001378656361\r
-1.........2.........3.......4....................5..........6........7.......8........ 1 -11.996154705745 2 0.089595739240 3 -10.202178290556 4 0.054914300199 5 -1.736816996815 6 -0.032603501689 7 -4.195445460669 8 0.001851431541\r
-1.........2.........3........4...................5..........6........7.......8........... 1 -12.257848313175 2 0.092590175903 3 -10.659297588498 4 0.060801061546 5 -2.636345521773 6 -0.022503755449 7 -4.759965806192 8 0.007771382648\r
-1.........2.........3........4...................5...........6............7........8........ 1 -12.259355038489 2 0.092549116189 3 -10.639209883812 4 0.060547018980 5 -2.686694919856 6 -0.021803626396 7 -4.793492695050 8 0.008110866391\r
-1.........2........3..........4....................5.........6...........7........8............ 1 -12.249881875797 2 0.092416898758 3 -10.672130776899 4 0.060971129165 5 -2.650573576969 6 -0.022247759312 7 -4.775642845095 8 0.007884230865\r
-1...........2.........3........4......................5...........6................7..............8................... 1 -12.245665107054 2 0.092363468788 3 -10.673080204933 4 0.060982828797 5 -2.645055980488 6 -0.022326293527 7 -4.772832315501 8 0.007851766610\r
-1..........2...............3................4......................5.................6..............7...............8.............\r
-#Number of iterations = 34, -2 Log likelihood = 46542.397795763849 \r
-# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\r
-12 -12.245160 0.092357 \r
-13 -10.672078 0.060971 \r
-21 -2.645815 -0.022320 \r
-23 -4.773208 0.007857 \r
-\r
-Calculation of the hessian matrix. Wait...\r
-12345678.12.13.14.15.16.17.18.23.24.25.26.27.28.34.35.36.37.38.45.46.47.48.56.57.58.67.68.78\r
-\r
-Inverting the hessian to get the covariance matrix. Wait...\r
-\r
-#Hessian matrix#\r
-2.314e+003 1.908e+005 4.106e+002 3.377e+004 -3.590e+002 -2.992e+004 -3.183e+002 -2.621e+004 \r
-1.908e+005 1.581e+007 3.349e+004 2.769e+006 -2.988e+004 -2.506e+006 -2.611e+004 -2.161e+006 \r
-4.106e+002 3.349e+004 8.125e+002 6.556e+004 -8.089e+001 -6.779e+003 3.862e+002 3.193e+004 \r
-3.377e+004 2.769e+006 6.556e+004 5.317e+006 -6.824e+003 -5.754e+005 3.190e+004 2.651e+006 \r
--3.590e+002 -2.988e+004 -8.089e+001 -6.824e+003 4.524e+002 3.800e+004 4.993e+001 4.166e+003 \r
--2.992e+004 -2.506e+006 -6.779e+003 -5.754e+005 3.800e+004 3.210e+006 4.173e+003 3.501e+005 \r
--3.183e+002 -2.611e+004 3.862e+002 3.190e+004 4.993e+001 4.173e+003 1.039e+003 8.943e+004 \r
--2.621e+004 -2.161e+006 3.193e+004 2.651e+006 4.166e+003 3.501e+005 8.943e+004 7.740e+006 \r
-# Scales (for hessian or gradient estimation)\r
-12 1.00000e-004 1.00000e-006\r
-13 1.00000e-004 1.00000e-006\r
-21 1.00000e-003 1.00000e-006\r
-23 1.00000e-004 1.00000e-005\r
-# Covariance matrix \r
-# 121 Var(a12)\r
-# 122 Cov(b12,a12) Var(b12)\r
-# ...\r
-# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\r
-#121 Var(a12)\r
-#122 Cov(b12,a12) Var(b12)\r
-#131 Cov(a13,a12) Cov(a13,b12) Var(a13)\r
-#132 Cov(b13,a12) Cov(b13,b12) Cov(b13,a13) Var(b13)\r
-#211 Cov(a21,a12) Cov(a21,b12) Cov(a21,a13) Cov(a21,b13) Var(a21)\r
-#212 Cov(b21,a12) Cov(b21,b12) Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\r
-#231 Cov(a23,a12) Cov(a23,b12) Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\r
-#232 Cov(b23,a12) Cov(b23,b12) Cov(b23,a13) Cov(b23,b13) Cov(b23,a21) Cov(b23,b21) Cov(b23,a23) Var(b23)\r
-121 1.12641e-001\r
-122 -1.35168e-003 1.63147e-005\r
-131 -6.15783e-002 7.47501e-004 3.20023e-001\r
-132 7.30656e-004 -8.95009e-006 -3.93444e-003 4.86922e-005\r
-211 8.34954e-002 -9.96445e-004 2.19213e-002 -2.86865e-004 4.89982e-001\r
-212 -9.95687e-004 1.19356e-005 -2.78360e-004 3.64465e-006 -5.80715e-003 6.91834e-005\r
-231 5.25828e-002 -5.99555e-004 -1.07947e-001 1.23483e-003 -4.52302e-004 7.66983e-006 2.43192e-001\r
-232 -5.99669e-004 6.88392e-006 1.27573e-003 -1.47509e-005 1.65541e-005 -2.31945e-007 -2.77700e-003 3.18981e-005\r
-begin-prev-date=1/1/1984 end-prev-date=1/6/1988 mov_average=0\r
-prevforecast=0 starting-proj-date=1/1/2000 final-proj-date=1/1/2000 mobil_average=0\r
-Computing stable prevalence: result on file 'plrbiaspar.txt' \r
-\r
-#************\r
-Computing pij: result on file 'pijrbiaspar.txt' \r
-Computing standard deviation of one-step probabilities: result on file 'probrbiaspar.txt' \r
-Computing matrix of variance covariance of one-step probabilities: result on file 'probcovrbiaspar.txt' \r
-and correlation matrix of one-step probabilities: result on file 'probcorrbiaspar.txt' \r
-65 13-12 mu 1.4593e-002 2.3279e-002 Var 3.0341e-006 3.1635e-006 cor -0.365 cov -1.1314e-006 Eig 4.232e-006 1.966e-006 1stv 0.687 -0.727 tan -1.059\r
-70 13-12 mu 1.9763e-002 3.6884e-002 Var 3.0384e-006 4.5353e-006 cor -0.388 cov -1.4408e-006 Eig 5.410e-006 2.163e-006 1stv 0.519 -0.855 tan -1.646\r
-75 13-12 mu 2.6743e-002 5.8392e-002 Var 2.6775e-006 5.6183e-006 cor -0.431 cov -1.6704e-006 Eig 6.373e-006 1.923e-006 1stv 0.412 -0.911 tan -2.213\r
-80 13-12 mu 3.6143e-002 9.2326e-002 Var 2.7937e-006 6.6302e-006 cor -0.475 cov -2.0432e-006 Eig 7.515e-006 1.909e-006 1stv 0.397 -0.918 tan -2.311\r
-85 13-12 mu 4.8753e-002 1.4570e-001 Var 7.0338e-006 1.5206e-005 cor -0.419 cov -4.3362e-006 Eig 1.708e-005 5.162e-006 1stv 0.396 -0.918 tan -2.316\r
-90 13-12 mu 6.5568e-002 2.2924e-001 Var 2.6664e-005 7.5815e-005 cor -0.360 cov -1.6178e-005 Eig 8.066e-005 2.182e-005 1stv 0.287 -0.958 tan -3.338\r
-95 13-12 mu 8.7783e-002 3.5906e-001 Var 9.1463e-005 3.7510e-004 cor -0.346 cov -6.4063e-005 Eig 3.889e-004 7.766e-005 1stv 0.211 -0.978 tan -4.643\r
-65 21-12 mu 1.9360e-001 2.3279e-002 Var 9.9237e-004 3.1635e-006 cor 0.346 cov 1.9394e-005 Eig 9.928e-004 2.783e-006 1stv 1.000 0.020 tan 0.020\r
-70 21-12 mu 1.7336e-001 3.6884e-002 Var 4.6644e-004 4.5353e-006 cor 0.341 cov 1.5681e-005 Eig 4.670e-004 4.004e-006 1stv 0.999 0.034 tan 0.034\r
-75 21-12 mu 1.5520e-001 5.8392e-002 Var 1.8929e-004 5.6183e-006 cor 0.328 cov 1.0707e-005 Eig 1.899e-004 4.996e-006 1stv 0.998 0.058 tan 0.058\r
-80 21-12 mu 1.3892e-001 9.2326e-002 Var 6.8114e-005 6.6302e-006 cor 0.297 cov 6.3116e-006 Eig 6.875e-005 5.989e-006 1stv 0.995 0.101 tan 0.102\r
-85 21-12 mu 1.2432e-001 1.4570e-001 Var 3.9653e-005 1.5206e-005 cor 0.283 cov 6.9398e-006 Eig 4.149e-005 1.337e-005 1stv 0.967 0.255 tan 0.264\r
-90 21-12 mu 1.1125e-001 2.2924e-001 Var 6.1785e-005 7.5815e-005 cor 0.316 cov 2.1606e-005 Eig 9.152e-005 4.608e-005 1stv 0.588 0.809 tan 1.376\r
-95 21-12 mu 9.9529e-002 3.5906e-001 Var 1.0730e-004 3.7510e-004 cor 0.332 cov 6.6677e-005 Eig 3.908e-004 9.162e-005 1stv 0.229 0.973 tan 4.252\r
-65 23-12 mu 1.6401e-001 2.3279e-002 Var 4.4369e-004 3.1635e-006 cor 0.367 cov 1.3733e-005 Eig 4.441e-004 2.736e-006 1stv 1.000 0.031 tan 0.031\r
-70 23-12 mu 1.7078e-001 3.6884e-002 Var 3.0364e-004 4.5353e-006 cor 0.390 cov 1.4477e-005 Eig 3.043e-004 3.836e-006 1stv 0.999 0.048 tan 0.048\r
-75 23-12 mu 1.7779e-001 5.8392e-002 Var 1.8621e-004 5.6183e-006 cor 0.426 cov 1.3769e-005 Eig 1.873e-004 4.574e-006 1stv 0.997 0.076 tan 0.076\r
-80 23-12 mu 1.8506e-001 9.2326e-002 Var 1.0029e-004 6.6302e-006 cor 0.453 cov 1.1693e-005 Eig 1.017e-004 5.192e-006 1stv 0.993 0.122 tan 0.123\r
-85 23-12 mu 1.9259e-001 1.4570e-001 Var 5.6316e-005 1.5206e-005 cor 0.359 cov 1.0514e-005 Eig 5.885e-005 1.267e-005 1stv 0.972 0.234 tan 0.241\r
-90 23-12 mu 2.0040e-001 2.2924e-001 Var 6.6423e-005 7.5815e-005 cor 0.257 cov 1.8270e-005 Eig 8.998e-005 5.226e-005 1stv 0.613 0.790 tan 1.290\r
-95 23-12 mu 2.0849e-001 3.5906e-001 Var 1.4472e-004 3.7510e-004 cor 0.241 cov 5.6144e-005 Eig 3.881e-004 1.318e-004 1stv 0.225 0.974 tan 4.334\r
-65 21-13 mu 1.9360e-001 1.4593e-002 Var 9.9237e-004 3.0341e-006 cor 0.034 cov 1.8605e-006 Eig 9.924e-004 3.031e-006 1stv 1.000 0.002 tan 0.002\r
-70 21-13 mu 1.7336e-001 1.9763e-002 Var 4.6644e-004 3.0384e-006 cor 0.024 cov 9.1482e-007 Eig 4.664e-004 3.037e-006 1stv 1.000 0.002 tan 0.002\r
-75 21-13 mu 1.5520e-001 2.6743e-002 Var 1.8929e-004 2.6775e-006 cor 0.012 cov 2.6204e-007 Eig 1.893e-004 2.677e-006 1stv 1.000 0.001 tan 0.001\r
-80 21-13 mu 1.3892e-001 3.6143e-002 Var 6.8114e-005 2.7937e-006 cor 0.017 cov 2.4067e-007 Eig 6.811e-005 2.793e-006 1stv 1.000 0.004 tan 0.004\r
-85 21-13 mu 1.2432e-001 4.8753e-002 Var 3.9653e-005 7.0338e-006 cor 0.080 cov 1.3331e-006 Eig 3.971e-005 6.979e-006 1stv 0.999 0.041 tan 0.041\r
-90 21-13 mu 1.1125e-001 6.5568e-002 Var 6.1785e-005 2.6664e-005 cor 0.103 cov 4.1739e-006 Eig 6.227e-005 2.617e-005 1stv 0.993 0.116 tan 0.117\r
-95 21-13 mu 9.9529e-002 8.7783e-002 Var 1.0730e-004 9.1463e-005 cor 0.096 cov 9.4967e-006 Eig 1.117e-004 8.702e-005 1stv 0.906 0.424 tan 0.468\r
-65 23-13 mu 1.6401e-001 1.4593e-002 Var 4.4369e-004 3.0341e-006 cor -0.456 cov -1.6739e-005 Eig 4.443e-004 2.399e-006 1stv 0.999 -0.038 tan -0.038\r
-70 23-13 mu 1.7078e-001 1.9763e-002 Var 3.0364e-004 3.0384e-006 cor -0.492 cov -1.4938e-005 Eig 3.044e-004 2.298e-006 1stv 0.999 -0.050 tan -0.050\r
-75 23-13 mu 1.7779e-001 2.6743e-002 Var 1.8621e-004 2.6775e-006 cor -0.552 cov -1.2318e-005 Eig 1.870e-004 1.854e-006 1stv 0.998 -0.067 tan -0.067\r
-80 23-13 mu 1.8506e-001 3.6143e-002 Var 1.0029e-004 2.7937e-006 cor -0.594 cov -9.9366e-006 Eig 1.013e-004 1.791e-006 1stv 0.995 -0.100 tan -0.101\r
-85 23-13 mu 1.9259e-001 4.8753e-002 Var 5.6316e-005 7.0338e-006 cor -0.523 cov -1.0409e-005 Eig 5.842e-005 4.925e-006 1stv 0.980 -0.199 tan -0.203\r
-90 23-13 mu 2.0040e-001 6.5568e-002 Var 6.6423e-005 2.6664e-005 cor -0.456 cov -1.9170e-005 Eig 7.416e-005 1.893e-005 1stv 0.927 -0.374 tan -0.404\r
-95 23-13 mu 2.0849e-001 8.7783e-002 Var 1.4472e-004 9.1463e-005 cor -0.404 cov -4.6471e-005 Eig 1.716e-004 6.453e-005 1stv 0.865 -0.501 tan -0.580\r
-65 23-21 mu 1.6401e-001 1.9360e-001 Var 4.4369e-004 9.9237e-004 cor -0.025 cov -1.6657e-005 Eig 9.929e-004 4.432e-004 1stv 0.030 -1.000 tan -32.971\r
-70 23-21 mu 1.7078e-001 1.7336e-001 Var 3.0364e-004 4.6644e-004 cor -0.022 cov -8.1118e-006 Eig 4.668e-004 3.032e-004 1stv 0.050 -0.999 tan -20.120\r
-75 23-21 mu 1.7779e-001 1.5520e-001 Var 1.8621e-004 1.8929e-004 cor -0.020 cov -3.6810e-006 Eig 1.917e-004 1.838e-004 1stv 0.554 -0.833 tan -1.503\r
-80 23-21 mu 1.8506e-001 1.3892e-001 Var 1.0029e-004 6.8114e-005 cor -0.027 cov -2.2125e-006 Eig 1.004e-004 6.796e-005 1stv 0.998 -0.068 tan -0.068\r
-85 23-21 mu 1.9259e-001 1.2432e-001 Var 5.6316e-005 3.9653e-005 cor -0.060 cov -2.8454e-006 Eig 5.679e-005 3.918e-005 1stv 0.986 -0.164 tan -0.166\r
-90 23-21 mu 2.0040e-001 1.1125e-001 Var 6.6423e-005 6.1785e-005 cor -0.077 cov -4.9431e-006 Eig 6.956e-005 5.864e-005 1stv 0.844 -0.536 tan -0.635\r
-95 23-21 mu 2.0849e-001 9.9529e-002 Var 1.4472e-004 1.0730e-004 cor -0.065 cov -8.0394e-006 Eig 1.464e-004 1.056e-004 1stv 0.979 -0.202 tan -0.206\r
-Computing Total LEs with variances: file 'trbiaspar.txt' \r
-Computing Health Expectancies: result on file 'erbiaspar.txt' \r
-Computing Variance-covariance of DFLEs: file 'vrbiaspar.txt' \r
-65|66|67|68|69|70|71|72|73|74|75|76|77|78|79|80|81|82|83|84|85|86|87|88|89|90|91|92|93|94|95|\r
-Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file 'prmorprev1-stablbased-rbiaspar.txt' \r
-End of Imach\r
-Local time at start Wed Jun 16 20:01:29 2004\r
-\r
-Local time at end Wed Jun 16 21:55:16 2004\r
-\r
-Total time used 0 day(s) 1 hour(s) 53 minute(s) 47 second(s)\r
-Total time was 6827 Sec.\r
+121 0.00000e+00
+122 0.00000e+00 0.00000e+00
+131 0.00000e+00 0.00000e+00 0.00000e+00
+132 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
+211 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
+212 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
+231 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
+232 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
+
+Total number of individuals= 8270, Agemin = 70.00, Agemax= 104.17
+
+Delay (in months) between two waves Min=1 Max=74 Mean=24.040080
+
+ Age 70 1.=665 loss[1]=5.1% 2.=0 loss[2]=NaNQ% 1.=631 prev[1]=100.0% 2.=0 prev[2]=0.0% 1-1=34 11=563 12=33 13=35 33=6
+Age 71 1.=663 loss[1]=5.7% 2.=2 loss[2]=0.0% 1.=625 prev[1]=99.7% 2.=2 prev[2]=0.3% 1-1=38 11=530 12=47 13=48 21=1 22=1 3-1=2 33=31
+Age 72 1.=1181 loss[1]=5.6% 2.=35 loss[2]=5.7% 1.=1115 prev[1]=97.1% 2.=33 prev[2]=2.9% 1-1=66 11=969 12=70 13=76 2-1=2 21=9 22=18 23=6 3-1=2 33=87
+Age 73 1.=1119 loss[1]=5.1% 2.=48 loss[2]=8.3% 1.=1062 prev[1]=96.0% 2.=44 prev[2]=4.0% 1-1=57 11=912 12=71 13=79 2-1=4 21=12 22=26 23=6 3-1=12 33=94
+Age 74 1.=1563 loss[1]=4.2% 2.=90 loss[2]=4.4% 1.=1497 prev[1]=94.6% 2.=86 prev[2]=5.4% 1-1=66 11=1277 12=104 13=116 2-1=4 21=30 22=41 23=15 3-1=4 33=125
+Age 75 1.=1463 loss[1]=6.2% 2.=98 loss[2]=7.1% 1.=1372 prev[1]=93.8% 2.=91 prev[2]=6.2% 1-1=91 11=1155 12=98 13=119 2-1=7 21=15 22=55 23=21 3-1=4 33=124
+Age 76 1.=1390 loss[1]=4.5% 2.=112 loss[2]=3.6% 1.=1328 prev[1]=92.5% 2.=108 prev[2]=7.5% 1-1=62 11=1090 12=111 13=127 2-1=4 21=25 22=54 23=29 3-1=4 33=142
+Age 77 1.=1271 loss[1]=5.0% 2.=101 loss[2]=5.9% 1.=1208 prev[1]=92.7% 2.=95 prev[2]=7.3% 1-1=63 11=962 12=131 13=115 2-1=6 21=24 22=52 23=19 3-1=7 33=145
+Age 78 1.=1166 loss[1]=4.9% 2.=122 loss[2]=4.1% 1.=1109 prev[1]=90.5% 2.=117 prev[2]=9.5% 1-1=57 11=894 12=111 13=104 2-1=5 21=21 22=75 23=21 3-1=4 33=146
+Age 79 1.=1045 loss[1]=5.7% 2.=133 loss[2]=5.3% 1.=985 prev[1]=88.7% 2.=126 prev[2]=11.3% 1-1=60 11=773 12=109 13=103 2-1=7 21=31 22=68 23=27 3-1=8 33=136
+Age 80 1.=986 loss[1]=4.1% 2.=128 loss[2]=3.1% 1.=946 prev[1]=88.4% 2.=124 prev[2]=11.6% 1-1=40 11=718 12=140 13=88 2-1=4 21=21 22=71 23=32 3-1=6 33=121
+Age 81 1.=872 loss[1]=4.9% 2.=130 loss[2]=3.8% 1.=829 prev[1]=86.9% 2.=125 prev[2]=13.1% 1-1=43 11=629 12=102 13=98 2-1=5 21=24 22=74 23=27 3-1=5 33=126
+Age 82 1.=803 loss[1]=4.4% 2.=146 loss[2]=4.1% 1.=768 prev[1]=84.6% 2.=140 prev[2]=15.4% 1-1=35 11=546 12=131 13=91 2-1=6 21=15 22=77 23=48 3-1=11 33=100
+Age 83 1.=726 loss[1]=6.5% 2.=116 loss[2]=0.9% 1.=679 prev[1]=85.5% 2.=115 prev[2]=14.5% 1-1=47 11=456 12=124 13=99 2-1=1 21=19 22=71 23=25 3-1=8 33=133
+Age 84 1.=622 loss[1]=5.6% 2.=147 loss[2]=4.1% 1.=587 prev[1]=80.6% 2.=141 prev[2]=19.4% 1-1=35 11=394 12=112 13=81 2-1=6 21=18 22=82 23=41 3-1=5 33=114
+Age 85 1.=526 loss[1]=4.4% 2.=127 loss[2]=6.3% 1.=503 prev[1]=80.9% 2.=119 prev[2]=19.1% 1-1=23 11=315 12=122 13=66 2-1=8 21=13 22=67 23=39 3-1=4 33=137
+Age 86 1.=464 loss[1]=5.2% 2.=130 loss[2]=6.2% 1.=440 prev[1]=78.3% 2.=122 prev[2]=21.7% 1-1=24 11=271 12=103 13=66 2-1=8 21=18 22=70 23=34 3-1=3 33=112
+Age 87 1.=372 loss[1]=4.8% 2.=143 loss[2]=2.8% 1.=354 prev[1]=71.8% 2.=139 prev[2]=28.2% 1-1=18 11=219 12=79 13=56 2-1=4 21=15 22=71 23=53 3-1=1 33=81
+Age 88 1.=283 loss[1]=3.9% 2.=164 loss[2]=6.7% 1.=272 prev[1]=64.0% 2.=153 prev[2]=36.0% 1-1=11 11=172 12=63 13=37 2-1=11 21=25 22=84 23=44 3-1=8 33=102
+Age 89 1.=227 loss[1]=3.5% 2.=152 loss[2]=4.6% 1.=219 prev[1]=60.2% 2.=145 prev[2]=39.8% 1-1=8 11=135 12=45 13=39 2-1=7 21=21 22=73 23=51 3-1=2 33=77
+Age 90 1.=181 loss[1]=3.9% 2.=143 loss[2]=4.9% 1.=174 prev[1]=56.1% 2.=136 prev[2]=43.9% 1-1=7 11=104 12=41 13=29 2-1=7 21=18 22=82 23=36 3-1=1 33=75
+Age 91 1.=146 loss[1]=4.1% 2.=109 loss[2]=8.3% 1.=140 prev[1]=58.3% 2.=100 prev[2]=41.7% 1-1=6 11=78 12=36 13=26 2-1=9 21=11 22=51 23=38 3-1=3 33=77
+Age 92 1.=114 loss[1]=6.1% 2.=101 loss[2]=2.0% 1.=107 prev[1]=51.9% 2.=99 prev[2]=48.1% 1-1=7 11=47 12=43 13=17 2-1=2 21=11 22=52 23=36 3-1=2 33=61
+Age 93 1.=78 loss[1]=3.8% 2.=89 loss[2]=12.4% 1.=75 prev[1]=49.0% 2.=78 prev[2]=51.0% 1-1=3 11=36 12=25 13=14 2-1=11 21=10 22=46 23=22 3-1=2 33=62
+Age 94 1.=51 loss[1]=3.9% 2.=71 loss[2]=1.4% 1.=49 prev[1]=41.2% 2.=70 prev[2]=58.8% 1-1=2 11=24 12=8 13=17 2-1=1 21=4 22=39 23=27 3-1=1 33=37
+Age 95 1.=38 loss[1]=5.3% 2.=57 loss[2]=5.3% 1.=36 prev[1]=40.0% 2.=54 prev[2]=60.0% 1-1=2 11=16 12=13 13=7 2-1=3 21=4 22=31 23=19 3-1=1 33=39
+Age 96 1.=25 loss[1]=4.0% 2.=43 loss[2]=4.7% 1.=24 prev[1]=36.9% 2.=41 prev[2]=63.1% 1-1=1 11=11 12=9 13=4 2-1=2 21=2 22=22 23=17 3-1=2 33=25
+Age 97 1.=11 loss[1]=0.0% 2.=36 loss[2]=8.3% 1.=11 prev[1]=25.0% 2.=33 prev[2]=75.0% 11=4 12=7 2-1=3 21=2 22=22 23=9 33=23
+Age 98 1.=5 loss[1]=0.0% 2.=21 loss[2]=0.0% 1.=5 prev[1]=19.2% 2.=21 prev[2]=80.8% 11=1 12=4 21=1 22=13 23=7 3-1=1 33=17
+Age 99 1.=6 loss[1]=0.0% 2.=14 loss[2]=0.0% 1.=6 prev[1]=30.0% 2.=14 prev[2]=70.0% 11=3 12=1 13=2 21=2 22=2 23=10 33=6
+Age 100 1.=2 loss[1]=0.0% 2.=9 loss[2]=0.0% 1.=2 prev[1]=18.2% 2.=9 prev[2]=81.8% 11=1 12=1 21=2 22=5 23=2 33=2
+Age 101 1.=2 loss[1]=50.0% 2.=0 loss[2]=NaNQ% 1.=1 prev[1]=100.0% 2.=0 prev[2]=0.0% 1-1=1 12=1 3-1=1 33=3
+Age 102 1.=2 loss[1]=0.0% 2.=1 loss[2]=0.0% 1.=2 prev[1]=66.7% 2.=1 prev[2]=33.3% 12=2 22=1 33=1
+Age 103 1.=0 loss[1]=NaNQ% 2.=0 loss[2]=NaNQ% 1.=0 prev[1]=NaNQ% 2.=0 prev[2]=NaNQ%
+Age 104 1.=0 loss[1]=NaNQ% 2.=0 loss[2]=NaNQ% 1.=0 prev[1]=NaNQ% 2.=0 prev[2]=NaNQ%
+Age 105 1.=0 loss[1]=NaNQ% 2.=0 loss[2]=NaNQ% 1.=0 prev[1]=NaNQ% 2.=0 prev[2]=NaNQ%
+Age 106 1.=0 loss[1]=NaNQ% 2.=0 loss[2]=NaNQ% 1.=0 prev[1]=NaNQ% 2.=0 prev[2]=NaNQ% -1-1=69 -11=718 -12=195 -13=261
+Total 1.=18068 loss[1]=5.0% 2.=2818 loss[2]=4.9% 1.=17161 prev[1]=86.5% 2.=2681 prev[2]=13.5% -1-1=69 -11=718 -12=195 -13=261 1-1=907 11=13305 12=2097 13=1759 2-1=137 21=424 22=1496 23=761 3-1=114 33=2567
+Powell
+ 1 0.000000000000 2 0.000000000000 3 0.000000000000 4 0.000000000000 5 0.000000000000 6 0.000000000000 7 0.000000000000 8 0.000000000000
+
+Considering the time needed for this last iteration #1: 5 seconds,
+ - if your program needs 10 iterations to converge, convergence will be
+ reached in 0 day(s) 0 hour(s) 0 minute(s) 45 second(s) i.e.
+ on Mon Oct 24 14:52:26 2005 (current time is Mon Oct 24 14:51:41 2005);
+ - if your program needs 20 iterations to converge, convergence will be
+ reached in 0 day(s) 0 hour(s) 1 minute(s) 35 second(s) i.e.
+ on Mon Oct 24 14:53:16 2005 (current time is Mon Oct 24 14:51:41 2005);
+ - if your program needs 30 iterations to converge, convergence will be
+ reached in 0 day(s) 0 hour(s) 2 minute(s) 25 second(s) i.e.
+ on Mon Oct 24 14:54:06 2005 (current time is Mon Oct 24 14:51:41 2005);
+1........2..............3.........4.......................5.....6............7.........8.............................. 1 8.981830530002 2 0.016741746069 3 -0.434889243858 4 0.000506810742 5 3.199437430882 6 -0.000133684844 7 -0.817356206705 8 0.000414700052
+
+Considering the time needed for this last iteration #2: 167 seconds,
+ - if your program needs 10 iterations to converge, convergence will be
+ reached in 0 day(s) 0 hour(s) 22 minute(s) 16 second(s) i.e.
+ on Mon Oct 24 15:16:44 2005 (current time is Mon Oct 24 14:54:28 2005);
+ - if your program needs 20 iterations to converge, convergence will be
+ reached in 0 day(s) 0 hour(s) 50 minute(s) 6 second(s) i.e.
+ on Mon Oct 24 15:44:34 2005 (current time is Mon Oct 24 14:54:28 2005);
+ - if your program needs 30 iterations to converge, convergence will be
+ reached in 0 day(s) 1 hour(s) 17 minute(s) 56 second(s) i.e.
+ on Mon Oct 24 16:12:24 2005 (current time is Mon Oct 24 14:54:28 2005);
+1...........2.....................3..........4..................5.................6................7..........8................. 1 -2.281804650756 2 0.011363116543 3 -3.509368523070 4 -0.009363669124 5 2.547946952776 6 -0.006890085832 7 -1.246147647315 8 -0.012650266592
+
+Considering the time needed for this last iteration #3: 168 seconds,
+ - if your program needs 10 iterations to converge, convergence will be
+ reached in 0 day(s) 0 hour(s) 19 minute(s) 36 second(s) i.e.
+ on Mon Oct 24 15:16:52 2005 (current time is Mon Oct 24 14:57:16 2005);
+ - if your program needs 20 iterations to converge, convergence will be
+ reached in 0 day(s) 0 hour(s) 47 minute(s) 36 second(s) i.e.
+ on Mon Oct 24 15:44:52 2005 (current time is Mon Oct 24 14:57:16 2005);
+ - if your program needs 30 iterations to converge, convergence will be
+ reached in 0 day(s) 1 hour(s) 15 minute(s) 36 second(s) i.e.
+ on Mon Oct 24 16:12:52 2005 (current time is Mon Oct 24 14:57:16 2005);
+1........2.................3......4....................5........6....................7..........8........... 1 -2.181985096129 2 0.011465880658 3 -4.732211491614 4 -0.008150559262 5 2.446857218233 6 -0.008350202510 7 -1.338377277831 8 -0.012700875334
+1........2................3..........4...................5.........6...................7..........8....................... 1 -3.070133451540 2 0.018029818494 3 -6.179866175818 4 0.001935898306 5 2.212009143103 6 -0.027638638041 7 -2.308991353528 8 -0.013146236293
+1........2...............3..........4....................5........6..........7..........8........... 1 -3.626502091197 2 0.020253035211 3 -6.684342507080 4 0.006057014157 5 2.123782483735 6 -0.032645573113 7 -2.451363857789 8 -0.013247681665
+1.........2................3..........4....................5........6..........7..........8................ 1 -7.192534317905 2 0.034624192693 3 -10.542205375135 4 0.036666250158 5 1.541870117892 6 -0.063020402356 7 -2.948321308915 8 -0.013800448747
+1.........2...........3.........4...................5.........6............7..........8......... 1 -7.695451703104 2 0.037194072253 3 -9.230251380079 4 0.039357187891 5 1.401560774610 6 -0.065175085233 7 -2.866616489626 8 -0.013803976993
+1.........2.............3..........4...................5.........6...........7...........8......... 1 -7.940212354544 2 0.039881323201 3 -9.188932954744 4 0.041398021268 5 1.337148135578 6 -0.067668349287 7 -2.901457910987 8 -0.013846848839
+1.........2...............3...........4...................5.........6...........7...........8.................. 1 -8.176431117205 2 0.042833923530 3 -9.304312328468 4 0.043720071441 5 1.276877306765 6 -0.070125167890 7 -2.891118730399 8 -0.013891797083
+1.........2.........3..........4...................5..........6...........7..........8........ 1 -8.179934732156 2 0.042989046121 3 -9.366297995893 4 0.044103933684 5 1.279115322988 6 -0.070236292085 7 -2.878917655261 8 -0.013898162887
+1..........2.........3..........4...................5..........6...........7..........8................ 1 -8.254585369807 2 0.044560894850 3 -9.868936732048 4 0.048207926200 5 1.293598356293 6 -0.070738582582 7 -2.797523985671 8 -0.013960095547
+1..........2.........3........4....................5..........6...........7.........8........ 1 -8.301539191723 2 0.045052305123 3 -10.022804846924 4 0.050130364363 5 1.294397184532 6 -0.070701522071 7 -2.801520599321 8 -0.013984314301
+1..........2.........3........4....................5..........6...........7.........8................ 1 -9.366193466838 2 0.057625368748 3 -13.302743404812 4 0.092879588144 5 1.298194338761 6 -0.069458719670 7 -2.845793360462 8 -0.014517392773
+1.........2.........3........4...................5..........6....................7........8......... 1 -9.460968984193 2 0.058999781798 3 -13.723675221324 4 0.097150765005 5 1.308211839961 6 -0.069448653825 7 -2.836187353406 8 -0.014578542733
+1..........2.........3........4...................5..................6...........7.........8.......... 1 -9.558132338168 2 0.060212099576 3 -13.942989603808 4 0.099311940480 5 1.302080125134 6 -0.069569168801 7 -2.798255305774 8 -0.014606029284
+1......................2.........3........4...................5...........6......................7.........8....... 1 -9.572161154893 2 0.060361245477 3 -13.929855173962 4 0.099310593326 5 1.298209054802 6 -0.069455399052 7 -2.795021923613 8 -0.014604875644
+1.........2.........3........4...................5..............6...........7.........8............. 1 -9.521658848729 2 0.059772467720 3 -13.378117941017 4 0.092719757070 5 1.273997949530 6 -0.068987502478 7 -2.776883693013 8 -0.014526513051
+1.........2.........3........4...................5..........6...........7........8....... 1 -9.561633452062 2 0.060333173985 3 -13.313444344667 4 0.091835856342 5 1.263732018431 6 -0.068847034820 7 -2.776256237312 8 -0.014524728372
+1.........2.........3........4...................5..........6..........7........8............... 1 -11.211177020816 2 0.080500005299 3 -11.537258013108 4 0.070983535362 5 0.867292040233 6 -0.064099822721 7 -2.823227325066 8 -0.014537371296
+1.........2.........3........4...................5..........6...........7........8........ 1 -11.325506728779 2 0.081619385497 3 -11.381316058273 4 0.068836396199 5 0.837536179182 6 -0.063930299171 7 -2.827086277323 8 -0.014528843884
+1.........2.........3........4......................5..........6...........7........8........... 1 -11.341676688719 2 0.081802878533 3 -11.416589557874 4 0.069266621366 5 0.836897464135 6 -0.063871223031 7 -2.826483099116 8 -0.014533771831
+1.....................2............3.........4....................5.................6...........7.........8........................ 1 -11.341583321858 2 0.081813100925 3 -11.417800327848 4 0.069285874759 5 0.836665337138 6 -0.063830701725 7 -2.824804546159 8 -0.014530472468
+1.................2.................3...........4........................5.............6..........7........8...... 1 -11.343601882043 2 0.081830552688 3 -11.402331269733 4 0.069097487762 5 0.835136563121 6 -0.063812998546 7 -2.824904482410 8 -0.014527159992
+1..............2.........3.........4...................5............6....................7..........8............. 1 -11.344108280017 2 0.081798969097 3 -11.289229702040 4 0.067698422410 5 0.821725110822 6 -0.063651576307 7 -2.828095083276 8 -0.014467808496
+1..........2.........3........4...................5..........6........7..........8............ 1 -11.346884442242 2 0.081798944160 3 -11.190636099860 4 0.066481588797 5 0.799901616320 6 -0.063393443465 7 -2.836778391487 8 -0.014350132999
+1.........2.........3........4...................5..........6........7...........8............ 1 -11.374550257257 2 0.082018917627 3 -10.813465698425 4 0.061852349060 5 0.649704022353 6 -0.061545565813 7 -2.904867373668 8 -0.013465068949
+1.........2.........3........4...................5..........6........7..........8............. 1 -11.497299557475 2 0.083382209466 3 -10.214520395463 4 0.054601478423 5 0.106321936126 6 -0.054800998817 7 -3.176294913042 8 -0.010075948370
+1.........2.........3........4...................5..........6........7........8............... 1 -11.841632967445 2 0.087600665563 3 -9.764976982488 4 0.049419193834 5 -1.249466269151 6 -0.038183184473 7 -3.898766321772 8 -0.001377882469
+1.........2.........3.......4....................5..........6........7.......8........ 1 -11.994458882977 2 0.089578157478 3 -10.199298537104 4 0.054876691393 5 -1.732627878219 6 -0.032656820997 7 -4.194520508882 8 0.001844755037
+1.........2.........3........4...................5..........6........7.......8......... 1 -12.258447292779 2 0.092595784728 3 -10.661249514758 4 0.060826936582 5 -2.635282790368 6 -0.022513797598 7 -4.762328938804 8 0.007796187842
+1..........2....................3........4...................5...........6...........7..........8........ 1 -12.259301101757 2 0.092547594732 3 -10.639466323537 4 0.060551352623 5 -2.684448479366 6 -0.021830603905 7 -4.795109470365 8 0.008128524946
+1..........2........3..........4....................5............6...........7............8.................. 1 -12.250033234263 2 0.092418316868 3 -10.671177063275 4 0.060960172903 5 -2.649386951711 6 -0.022262295734 7 -4.777729640313 8 0.007908146901
+1...........2..........3..........4....................5............6............7..............8................. 1 -12.245968180439 2 0.092366839432 3 -10.671951574439 4 0.060969690741 5 -2.644234071218 6 -0.022336213263 7 -4.775102360558 8 0.007877895201
+1...........2..........................3...................4.........................5......................6...................7............8..................
+#Number of iterations = 34, -2 Log likelihood = 46542.378402526519
+# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...
+12 -12.245504 0.092361
+13 -10.670953 0.060958
+21 -2.645034 -0.022329
+23 -4.775501 0.007884
+
+Calculation of the hessian matrix. Wait...
+12345678.12.13.14.15.16.17.18.23.24.25.26.27.28.34.35.36.37.38.45.46.47.48.56.57.58.67.68.78
+
+Inverting the hessian to get the covariance matrix. Wait...
+
+#Hessian matrix#
+2.314e+03 1.908e+05 4.106e+02 3.377e+04 -3.590e+02 -2.993e+04 -3.182e+02 -2.620e+04
+1.908e+05 1.581e+07 3.349e+04 2.769e+06 -2.988e+04 -2.505e+06 -2.611e+04 -2.161e+06
+4.106e+02 3.349e+04 8.126e+02 6.556e+04 -8.087e+01 -6.783e+03 3.862e+02 3.192e+04
+3.377e+04 2.769e+06 6.556e+04 5.317e+06 -6.823e+03 -5.756e+05 3.190e+04 2.651e+06
+-3.590e+02 -2.988e+04 -8.087e+01 -6.823e+03 4.524e+02 3.800e+04 4.993e+01 4.166e+03
+-2.993e+04 -2.505e+06 -6.783e+03 -5.756e+05 3.800e+04 3.210e+06 4.173e+03 3.500e+05
+-3.182e+02 -2.611e+04 3.862e+02 3.190e+04 4.993e+01 4.173e+03 1.039e+03 8.943e+04
+-2.620e+04 -2.161e+06 3.192e+04 2.651e+06 4.166e+03 3.500e+05 8.943e+04 7.740e+06
+# Scales (for hessian or gradient estimation)
+12 1.00000e-04 1.00000e-06
+13 1.00000e-04 1.00000e-06
+21 1.00000e-03 1.00000e-06
+23 1.00000e-04 1.00000e-05
+# Covariance matrix
+# 121 Var(a12)
+# 122 Cov(b12,a12) Var(b12)
+# ...
+# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)
+#121 Var(a12)
+#122 Cov(b12,a12) Var(b12)
+#131 Cov(a13,a12) Cov(a13,b12) Var(a13)
+#132 Cov(b13,a12) Cov(b13,b12) Cov(b13,a13) Var(b13)
+#211 Cov(a21,a12) Cov(a21,b12) Cov(a21,a13) Cov(a21,b13) Var(a21)
+#212 Cov(b21,a12) Cov(b21,b12) Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)
+#231 Cov(a23,a12) Cov(a23,b12) Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)
+#232 Cov(b23,a12) Cov(b23,b12) Cov(b23,a13) Cov(b23,b13) Cov(b23,a21) Cov(b23,b21) Cov(b23,a23) Var(b23)
+121 1.13401e-01
+122 -1.36090e-03 1.64264e-05
+131 -6.89393e-02 8.35716e-04 3.31264e-01
+132 8.21021e-04 -1.00329e-05 -4.07026e-03 5.03323e-05
+211 7.49121e-02 -8.92959e-04 1.95088e-02 -2.56008e-04 4.75336e-01
+212 -8.93092e-04 1.06987e-05 -2.49893e-04 3.28027e-06 -5.63203e-03 6.70896e-05
+231 5.58947e-02 -6.39542e-04 -1.16708e-01 1.34217e-03 -9.40960e-04 1.38147e-05 2.47512e-01
+232 -6.38539e-04 7.35309e-06 1.37680e-03 -1.59888e-05 2.13084e-05 -2.92279e-07 -2.82744e-03 3.24870e-05
+begin-prev-date=1/1/1984 end-prev-date=1/6/1988 mov_average=0
+prevforecast=0 starting-proj-date=1/1/2000 final-proj-date=1/1/2000 mobil_average=0
+Computing stable prevalence: result on file 'plrbiaspar.txt'
+
+#************
+Computing pij: result on file 'pijrbiaspar.txt'
+Computing standard deviation of one-step probabilities: result on file 'probrbiaspar.txt'
+Computing matrix of variance covariance of one-step probabilities: result on file 'probcovrbiaspar.txt'
+and correlation matrix of one-step probabilities: result on file 'probcorrbiaspar.txt'
+65 13-12 mu 1.4597e-02 2.3277e-02 Var 3.1453e-06 3.1816e-06 cor -0.393 cov -1.2429e-06 Eig 4.407e-06 1.920e-06 1stv 0.702 -0.712 tan -1.015
+70 13-12 mu 1.9767e-02 3.6881e-02 Var 3.1424e-06 4.5584e-06 cor -0.413 cov -1.5617e-06 Eig 5.565e-06 2.136e-06 1stv 0.542 -0.841 tan -1.551
+75 13-12 mu 2.6747e-02 5.8389e-02 Var 2.7455e-06 5.6383e-06 cor -0.448 cov -1.7608e-06 Eig 6.471e-06 1.913e-06 1stv 0.427 -0.904 tan -2.116
+80 13-12 mu 3.6146e-02 9.2323e-02 Var 2.8030e-06 6.6320e-06 cor -0.477 cov -2.0574e-06 Eig 7.528e-06 1.907e-06 1stv 0.399 -0.917 tan -2.297
+85 13-12 mu 4.8754e-02 1.4570e-01 Var 7.0382e-06 1.5211e-05 cor -0.422 cov -4.3687e-06 Eig 1.711e-05 5.143e-06 1stv 0.398 -0.917 tan -2.305
+90 13-12 mu 6.5564e-02 2.2924e-01 Var 2.7005e-05 7.6142e-05 cor -0.376 cov -1.7053e-05 Eig 8.148e-05 2.167e-05 1stv 0.299 -0.954 tan -3.195
+95 13-12 mu 8.7773e-02 3.5907e-01 Var 9.3321e-05 3.7748e-04 cor -0.369 cov -6.9221e-05 Eig 3.934e-04 7.736e-05 1stv 0.225 -0.974 tan -4.336
+65 21-12 mu 1.9364e-01 2.3277e-02 Var 9.6637e-04 3.1816e-06 cor 0.317 cov 1.7554e-05 Eig 9.667e-04 2.862e-06 1stv 1.000 0.018 tan 0.018
+70 21-12 mu 1.7338e-01 3.6881e-02 Var 4.5522e-04 4.5584e-06 cor 0.314 cov 1.4302e-05 Eig 4.557e-04 4.105e-06 1stv 0.999 0.032 tan 0.032
+75 21-12 mu 1.5521e-01 5.8389e-02 Var 1.8567e-04 5.6383e-06 cor 0.307 cov 9.9468e-06 Eig 1.862e-04 5.090e-06 1stv 0.998 0.055 tan 0.055
+80 21-12 mu 1.3892e-01 9.2323e-02 Var 6.7602e-05 6.6320e-06 cor 0.290 cov 6.1458e-06 Eig 6.822e-05 6.019e-06 1stv 0.995 0.099 tan 0.100
+85 21-12 mu 1.2432e-01 1.4570e-01 Var 3.9595e-05 1.5211e-05 cor 0.281 cov 6.8846e-06 Eig 4.140e-05 1.340e-05 1stv 0.967 0.254 tan 0.263
+90 21-12 mu 1.1124e-01 2.2924e-01 Var 6.0749e-05 7.6142e-05 cor 0.298 cov 2.0238e-05 Eig 9.010e-05 4.679e-05 1stv 0.568 0.823 tan 1.450
+95 21-12 mu 9.9518e-02 3.5907e-01 Var 1.0464e-04 3.7748e-04 cor 0.306 cov 6.0852e-05 Eig 3.904e-04 9.169e-05 1stv 0.208 0.978 tan 4.697
+65 23-12 mu 1.6392e-01 2.3277e-02 Var 4.4973e-04 3.1816e-06 cor 0.380 cov 1.4384e-05 Eig 4.502e-04 2.719e-06 1stv 0.999 0.032 tan 0.032
+70 23-12 mu 1.7070e-01 3.6881e-02 Var 3.0743e-04 4.5584e-06 cor 0.402 cov 1.5054e-05 Eig 3.082e-04 3.812e-06 1stv 0.999 0.050 tan 0.050
+75 23-12 mu 1.7774e-01 5.8389e-02 Var 1.8810e-04 5.6383e-06 cor 0.435 cov 1.4152e-05 Eig 1.892e-04 4.547e-06 1stv 0.997 0.077 tan 0.077
+80 23-12 mu 1.8502e-01 9.2323e-02 Var 1.0082e-04 6.6320e-06 cor 0.456 cov 1.1795e-05 Eig 1.023e-04 5.178e-06 1stv 0.992 0.122 tan 0.123
+85 23-12 mu 1.9258e-01 1.4570e-01 Var 5.6251e-05 1.5211e-05 cor 0.358 cov 1.0482e-05 Eig 5.877e-05 1.269e-05 1stv 0.972 0.234 tan 0.241
+90 23-12 mu 2.0041e-01 2.2924e-01 Var 6.6788e-05 7.6142e-05 cor 0.266 cov 1.8971e-05 Eig 9.100e-05 5.193e-05 1stv 0.617 0.787 tan 1.276
+95 23-12 mu 2.0853e-01 3.5907e-01 Var 1.4685e-04 3.7748e-04 cor 0.256 cov 6.0241e-05 Eig 3.923e-04 1.321e-04 1stv 0.238 0.971 tan 4.074
+65 21-13 mu 1.9364e-01 1.4597e-02 Var 9.6637e-04 3.1453e-06 cor 0.029 cov 1.6142e-06 Eig 9.664e-04 3.143e-06 1stv 1.000 0.002 tan 0.002
+70 21-13 mu 1.7338e-01 1.9767e-02 Var 4.5522e-04 3.1424e-06 cor 0.021 cov 7.7634e-07 Eig 4.552e-04 3.141e-06 1stv 1.000 0.002 tan 0.002
+75 21-13 mu 1.5521e-01 2.6747e-02 Var 1.8567e-04 2.7455e-06 cor 0.010 cov 2.1716e-07 Eig 1.857e-04 2.745e-06 1stv 1.000 0.001 tan 0.001
+80 21-13 mu 1.3892e-01 3.6146e-02 Var 6.7602e-05 2.8030e-06 cor 0.018 cov 2.4908e-07 Eig 6.760e-05 2.802e-06 1stv 1.000 0.004 tan 0.004
+85 21-13 mu 1.2432e-01 4.8754e-02 Var 3.9595e-05 7.0382e-06 cor 0.079 cov 1.3170e-06 Eig 3.965e-05 6.985e-06 1stv 0.999 0.040 tan 0.040
+90 21-13 mu 1.1124e-01 6.5564e-02 Var 6.0749e-05 2.7005e-05 cor 0.099 cov 4.0068e-06 Eig 6.122e-05 2.654e-05 1stv 0.993 0.116 tan 0.117
+95 21-13 mu 9.9518e-02 8.7773e-02 Var 1.0464e-04 9.3321e-05 cor 0.091 cov 8.9980e-06 Eig 1.096e-04 8.835e-05 1stv 0.875 0.483 tan 0.552
+65 23-13 mu 1.6392e-01 1.4597e-02 Var 4.4973e-04 3.1453e-06 cor -0.473 cov -1.7779e-05 Eig 4.504e-04 2.439e-06 1stv 0.999 -0.040 tan -0.040
+70 23-13 mu 1.7070e-01 1.9767e-02 Var 3.0743e-04 3.1424e-06 cor -0.506 cov -1.5725e-05 Eig 3.082e-04 2.332e-06 1stv 0.999 -0.051 tan -0.052
+75 23-13 mu 1.7774e-01 2.6747e-02 Var 1.8810e-04 2.7455e-06 cor -0.561 cov -1.2754e-05 Eig 1.890e-04 1.872e-06 1stv 0.998 -0.068 tan -0.068
+80 23-13 mu 1.8502e-01 3.6146e-02 Var 1.0082e-04 2.8030e-06 cor -0.595 cov -1.0008e-05 Eig 1.018e-04 1.792e-06 1stv 0.995 -0.101 tan -0.101
+85 23-13 mu 1.9258e-01 4.8754e-02 Var 5.6251e-05 7.0382e-06 cor -0.519 cov -1.0318e-05 Eig 5.833e-05 4.963e-06 1stv 0.980 -0.197 tan -0.201
+90 23-13 mu 2.0041e-01 6.5564e-02 Var 6.6788e-05 2.7005e-05 cor -0.461 cov -1.9572e-05 Eig 7.480e-05 1.899e-05 1stv 0.925 -0.379 tan -0.409
+95 23-13 mu 2.0853e-01 8.7773e-02 Var 1.4685e-04 9.3321e-05 cor -0.418 cov -4.8891e-05 Eig 1.758e-04 6.435e-05 1stv 0.860 -0.510 tan -0.593
+65 23-21 mu 1.6392e-01 1.9364e-01 Var 4.4973e-04 9.6637e-04 cor -0.027 cov -1.7471e-05 Eig 9.670e-04 4.491e-04 1stv 0.034 -0.999 tan -29.605
+70 23-21 mu 1.7070e-01 1.7338e-01 Var 3.0743e-04 4.5522e-04 cor -0.023 cov -8.6175e-06 Eig 4.557e-04 3.069e-04 1stv 0.058 -0.998 tan -17.208
+75 23-21 mu 1.7774e-01 1.5521e-01 Var 1.8810e-04 1.8567e-04 cor -0.021 cov -3.9354e-06 Eig 1.910e-04 1.828e-04 1stv 0.805 -0.594 tan -0.738
+80 23-21 mu 1.8502e-01 1.3892e-01 Var 1.0082e-04 6.7602e-05 cor -0.028 cov -2.2822e-06 Eig 1.010e-04 6.745e-05 1stv 0.998 -0.068 tan -0.068
+85 23-21 mu 1.9258e-01 1.2432e-01 Var 5.6251e-05 3.9595e-05 cor -0.059 cov -2.8004e-06 Eig 5.671e-05 3.914e-05 1stv 0.987 -0.161 tan -0.164
+90 23-21 mu 2.0041e-01 1.1124e-01 Var 6.6788e-05 6.0749e-05 cor -0.076 cov -4.8520e-06 Eig 6.948e-05 5.805e-05 1stv 0.874 -0.486 tan -0.556
+95 23-21 mu 2.0853e-01 9.9518e-02 Var 1.4685e-04 1.0464e-04 cor -0.064 cov -7.9663e-06 Eig 1.483e-04 1.032e-04 1stv 0.984 -0.179 tan -0.182
+Computing Total LEs with variances: file 'trbiaspar.txt'
+Computing Health Expectancies: result on file 'erbiaspar.txt'
+Computing Variance-covariance of DFLEs: file 'vrbiaspar.txt'
+65|66|67|68|69|70|71|72|73|74|75|76|77|78|79|80|81|82|83|84|85|86|87|88|89|90|91|92|93|94|95|
+Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file 'prmorprev1-stablbased-rbiaspar.txt'
+End of Imach
+Local time at start Mon Oct 24 14:51:36 2005
+
+Local time at end Mon Oct 24 16:19:18 2005
+
+Total time used 0 day(s) 1 hour(s) 27 minute(s) 42 second(s)
+Total time was 5262 Sec.
# Imach version 0.97b, June 2004, INED-EUROREVES \r
-title=1st_example datafile=data1.txt lastobs=8600 firstpass=1 lastpass=4\r
-ftol=1.000000e-008 stepm=1 ncovcol=2 nlstate=2 ndeath=1 maxwav=4 mle=1 weight=0\r
-model=.\r
+title=1st_example datafile=data1.txt lastobs=8600 firstpass=1 lastpass=4
+ftol=1.000000e-08 stepm=1 ncovcol=2 nlstate=2 ndeath=1 maxwav=4 mle=1 weight=0
+model=.
# Parameters\r
-12 0.000000 0.000000\r
-13 0.000000 0.000000\r
-21 0.000000 0.000000\r
-23 0.000000 0.000000\r
+12 0.000000 0.000000
+13 0.000000 0.000000
+21 0.000000 0.000000
+23 0.000000 0.000000
# Scales\r
-12 0.000000e+000 0.000000e+000\r
-13 0.000000e+000 0.000000e+000\r
-21 0.000000e+000 0.000000e+000\r
-23 0.000000e+000 0.000000e+000\r
+12 0.000000e+00 0.000000e+00
+13 0.000000e+00 0.000000e+00
+21 0.000000e+00 0.000000e+00
+23 0.000000e+00 0.000000e+00
#covariance matrix#\r
-121 0.00000e+000\r
-122 0.00000e+000 0.00000e+000\r
-131 0.00000e+000 0.00000e+000 0.00000e+000\r
-132 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
-211 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
-212 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
-231 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
-232 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000 0.00000e+000\r
+121 0.00000e+00
+122 0.00000e+00 0.00000e+00
+131 0.00000e+00 0.00000e+00 0.00000e+00
+132 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
+211 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
+212 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
+231 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
+232 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\r
-agemin=70 agemax=95 bage=65 fage=95 estepm=1\r
+agemin=70 agemax=95 bage=65 fage=95 estepm=1
# Observed prevalence period\r
-begin-prev-date=1/1/1984 end-prev-date=1/6/1988 mov_average=0\r
-pop_based=0\r
-prevforecast=0 starting-proj-date=1/1/2000 final-proj-date=1/1/2000 mobil_average=0\r
+begin-prev-date=1/1/1984 end-prev-date=1/6/1988 mov_average=0
+pop_based=0
+prevforecast=0 starting-proj-date=1/1/2000 final-proj-date=1/1/2000 mobil_average=0
-#Imach version 0.07a, May 2004, INED-EUROREVES \r
-#Number of iterations = 34, -2 Log likelihood = 46542.397795763849 \r
-title=1st_example datafile=data1.txt lastobs=8600 firstpass=1 lastpass=4\r
-ftol=1.000000e-008 stepm=1 ncovcol=2 nlstate=2 ndeath=1 maxwav=4 mle= 0 weight=0\r
-model=.\r
-# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\r
-12 -12.245160 0.092357 \r
-13 -10.672078 0.060971 \r
-21 -2.645815 -0.022320 \r
-23 -4.773208 0.007857 \r
-# Scales (for hessian or gradient estimation)\r
-12 1.00000e-004 1.00000e-006\r
-13 1.00000e-004 1.00000e-006\r
-21 1.00000e-003 1.00000e-006\r
-23 1.00000e-004 1.00000e-005\r
-# Covariance matrix \r
-# 121 Var(a12)\r
-# 122 Cov(b12,a12) Var(b12)\r
-# ...\r
-# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\r
-#121 Var(a12)\r
-#122 Cov(b12,a12) Var(b12)\r
-#131 Cov(a13,a12) Cov(a13,b12) Var(a13)\r
-#132 Cov(b13,a12) Cov(b13,b12) Cov(b13,a13) Var(b13)\r
-#211 Cov(a21,a12) Cov(a21,b12) Cov(a21,a13) Cov(a21,b13) Var(a21)\r
-#212 Cov(b21,a12) Cov(b21,b12) Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\r
-#231 Cov(a23,a12) Cov(a23,b12) Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\r
-#232 Cov(b23,a12) Cov(b23,b12) Cov(b23,a13) Cov(b23,b13) Cov(b23,a21) Cov(b23,b21) Cov(b23,a23) Var(b23)\r
-121 1.12641e-001\r
-122 -1.35168e-003 1.63147e-005\r
-131 -6.15783e-002 7.47501e-004 3.20023e-001\r
-132 7.30656e-004 -8.95009e-006 -3.93444e-003 4.86922e-005\r
-211 8.34954e-002 -9.96445e-004 2.19213e-002 -2.86865e-004 4.89982e-001\r
-212 -9.95687e-004 1.19356e-005 -2.78360e-004 3.64465e-006 -5.80715e-003 6.91834e-005\r
-231 5.25828e-002 -5.99555e-004 -1.07947e-001 1.23483e-003 -4.52302e-004 7.66983e-006 2.43192e-001\r
-232 -5.99669e-004 6.88392e-006 1.27573e-003 -1.47509e-005 1.65541e-005 -2.31945e-007 -2.77700e-003 3.18981e-005\r
-# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\r
-agemin=70 agemax=95 bage=65 fage=95 estepm=1\r
-begin-prev-date=1/1/1984 end-prev-date=1/6/1988 mov_average=0\r
-pop_based=0\r
-prevforecast=0 starting-proj-date=1/1/2000 final-proj-date=1/1/2000 mobil_average=0\r
+#Imach version 0.98, September 2005, INED-EUROREVES
+#Number of iterations = 34, -2 Log likelihood = 46542.378402526519
+title=1st_example datafile=data1.txt lastobs=8600 firstpass=1 lastpass=4
+ftol=1.000000e-08 stepm=1 ncovcol=2 nlstate=2 ndeath=1 maxwav=4 mle= 0 weight=0
+model=.
+# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...
+12 -12.245504 0.092361
+13 -10.670953 0.060958
+21 -2.645034 -0.022329
+23 -4.775501 0.007884
+# Scales (for hessian or gradient estimation)
+12 1.00000e-04 1.00000e-06
+13 1.00000e-04 1.00000e-06
+21 1.00000e-03 1.00000e-06
+23 1.00000e-04 1.00000e-05
+# Covariance matrix
+# 121 Var(a12)
+# 122 Cov(b12,a12) Var(b12)
+# ...
+# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)
+#121 Var(a12)
+#122 Cov(b12,a12) Var(b12)
+#131 Cov(a13,a12) Cov(a13,b12) Var(a13)
+#132 Cov(b13,a12) Cov(b13,b12) Cov(b13,a13) Var(b13)
+#211 Cov(a21,a12) Cov(a21,b12) Cov(a21,a13) Cov(a21,b13) Var(a21)
+#212 Cov(b21,a12) Cov(b21,b12) Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)
+#231 Cov(a23,a12) Cov(a23,b12) Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)
+#232 Cov(b23,a12) Cov(b23,b12) Cov(b23,a13) Cov(b23,b13) Cov(b23,a21) Cov(b23,b21) Cov(b23,a23) Var(b23)
+121 1.13401e-01
+122 -1.36090e-03 1.64264e-05
+131 -6.89393e-02 8.35716e-04 3.31264e-01
+132 8.21021e-04 -1.00329e-05 -4.07026e-03 5.03323e-05
+211 7.49121e-02 -8.92959e-04 1.95088e-02 -2.56008e-04 4.75336e-01
+212 -8.93092e-04 1.06987e-05 -2.49893e-04 3.28027e-06 -5.63203e-03 6.70896e-05
+231 5.58947e-02 -6.39542e-04 -1.16708e-01 1.34217e-03 -9.40960e-04 1.38147e-05 2.47512e-01
+232 -6.38539e-04 7.35309e-06 1.37680e-03 -1.59888e-05 2.13084e-05 -2.92279e-07 -2.82744e-03 3.24870e-05
+# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).
+agemin=70 agemax=95 bage=65 fage=95 estepm=1
+begin-prev-date=1/1/1984 end-prev-date=1/6/1988 mov_average=0
+pop_based=0
+prevforecast=0 starting-proj-date=1/1/2000 final-proj-date=1/1/2000 mobil_average=0
git://henry.ined.fr / .git / commitdiff