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Annotation of imach/tests/testV1V2.imach, revision 1.2

1.2     ! brouard     1: #$Revision: 1.1 $ $Date: 2015/09/16 08:50:20 $
1.1       brouard     2: # ADL ANALYSIS USING SABE 2000 2006 AND 2010 by sex basic model with weights
                      3: #
1.2     ! brouard     4: title=testV1V2 datafile=data/data2.txt lastobs=2500 firstpass=1 lastpass=3
        !             5: ftol=1.e-08 stepm=24 ncovcol=2 nqv=0 ntv=0 nqtv=0 nlstate=2 ndeath=1 maxwav=3 mle=1 weight=1
1.1       brouard     6: model=1+age+V1+V2.
                      7: # Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...
                      8: 12   -8.1682774    0.0847996  0.0  0.2682606 
                      9: 13   -8.1383206    0.0766705  0.0  0.4020807 
                     10: 21    2.3321826   -0.0492910  0.0 -0.4643334 
                     11: 23   -8.2079189    0.0888604  0.0  0.1497600 
                     12: # Scales (for hessian or gradient estimation)
                     13: 12 0. 0. 0. 0.
                     14: 13 0. 0. 0. 0.
                     15: 21 0. 0. 0. 0.
                     16: 23 0. 0. 0. 0.
                     17: # Covariance matrix
                     18: #121 Var(a12)
                     19: #122 Cov(b12,a12) Var(b12)
                     20: #123 Cov(c12,a12) Cov(c12,b12) Var(c12)
                     21: #124 Cov(d12,a12) Cov(d12,b12) Cov(d12,c12) Var(d12)
                     22: #131 Cov(a13,a12) Cov(a13,b12) Cov(a13,c12) Cov(a13,d12) Var(a13)
                     23: #132 Cov(b13,a12) Cov(b13,b12) Cov(b13,c12) Cov(b13,d12) Cov(b13,a13) Var(b13)
                     24: #133 Cov(c13,a12) Cov(c13,b12) Cov(c13,c12) Cov(c13,d12) Cov(c13,a13) Cov(c13,b13) Var(c13)
                     25: #134 Cov(d13,a12) Cov(d13,b12) Cov(d13,c12) Cov(d13,d12) Cov(d13,a13) Cov(d13,b13) Cov(d13,c13) Var(d13)
                     26: #211 Cov(a21,a12) Cov(a21,b12) Cov(a21,c12) Cov(a21,d12) Cov(a21,a13) Cov(a21,b13) Cov(a21,c13) Cov(a21,d13) Var(a21)
                     27: #212 Cov(b21,a12) Cov(b21,b12) Cov(b21,c12) Cov(b21,d12) Cov(b21,a13) Cov(b21,b13) Cov(b21,c13) Cov(b21,d13) Cov(b21,a21) Var(b21)
                     28: #213 Cov(c21,a12) Cov(c21,b12) Cov(c21,c12) Cov(c21,d12) Cov(c21,a13) Cov(c21,b13) Cov(c21,c13) Cov(c21,d13) Cov(c21,a21) Cov(c21,b21) Var(c21)
                     29: #214 Cov(d21,a12) Cov(d21,b12) Cov(d21,c12) Cov(d21,d12) Cov(d21,a13) Cov(d21,b13) Cov(d21,c13) Cov(d21,d13) Cov(d21,a21) Cov(d21,b21) Cov(d21,c21) Var(d21)
                     30: #231 Cov(a23,a12) Cov(a23,b12) Cov(a23,c12) Cov(a23,d12) Cov(a23,a13) Cov(a23,b13) Cov(a23,c13) Cov(a23,d13) Cov(a23,a21) Cov(a23,b21) Cov(a23,c21) Cov(a23,d21) Var(a23)
                     31: #232 Cov(b23,a12) Cov(b23,b12) Cov(b23,c12) Cov(b23,d12) Cov(b23,a13) Cov(b23,b13) Cov(b23,c13) Cov(b23,d13) Cov(b23,a21) Cov(b23,b21) Cov(b23,c21) Cov(b23,d21) Cov(b23,a23) Var(b23)
                     32: #233 Cov(c23,a12) Cov(c23,b12) Cov(c23,c12) Cov(c23,d12) Cov(c23,a13) Cov(c23,b13) Cov(c23,c13) Cov(c23,d13) Cov(c23,a21) Cov(c23,b21) Cov(c23,c21) Cov(c23,d21) Cov(c23,a23) Cov(c23,b23) Var(c23)
                     33: #234 Cov(d23,a12) Cov(d23,b12) Cov(d23,c12) Cov(d23,d12) Cov(d23,a13) Cov(d23,b13) Cov(d23,c13) Cov(d23,d13) Cov(d23,a21) Cov(d23,b21) Cov(d23,c21) Cov(d23,d21) Cov(d23,a23) Cov(d23,b23) Cov(d23,c23) Var(d23)
                     34: 121 0.
                     35: 122 0. 0.
                     36: 123 0. 0. 0.
                     37: 124 0. 0. 0. 0.
                     38: 131 0. 0. 0. 0. 0.
                     39: 132 0. 0. 0. 0. 0. 0.
                     40: 133 0. 0. 0. 0. 0. 0. 0.
                     41: 134 0. 0. 0. 0. 0. 0. 0. 0.
                     42: 211 0. 0. 0. 0. 0. 0. 0. 0. 0.
                     43: 212 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
                     44: 213 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
                     45: 214 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
                     46: 231 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
                     47: 232 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
                     48: 233 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
                     49: 234 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
                     50: # agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).
1.2     ! brouard    51: agemin=60 agemax=95 bage=60 fage=95 estepm=24 ftolpl=6e-5
1.1       brouard    52: # Observed prevalence period
1.2     ! brouard    53: begin-prev-date=1/1/2000 end-prev-date=12/12/2006 mov_average=0
1.1       brouard    54: # Health expectancies computed from stable (period) prevalence (pop_based=0) or population based (1)
                     55: pop_based=1
                     56: # Prevalence forecasting
1.2     ! brouard    57: #prevforecast=0 starting-proj-date=1/1/1998 final-proj-date=1/1/2002 mobil_average=1
        !            58: prevforecast=1 yearsfproj=10 mobil_average=0
        !            59: prevbackcast=1 yearsbproj=10 mobil_average=1
        !            60: result:V1=0 V2=0
        !            61: result:V1=1 V2=0
        !            62: result:V1=1 V2=1
        !            63: result:V1=0 V2=0