--- imach096d/doc/imach.htm 2002/03/11 14:18:06 1.8 +++ imach096d/doc/imach.htm 2002/03/11 22:26:00 1.10 @@ -1,4 +1,4 @@ - + @@ -425,6 +425,45 @@ warranty!):

23 0.0 0.0 +

In order to speed up the convergence you can make a first run with +a large stepm i.e stepm=12 or 24 and then decrease the stepm until +stepm=1 month. If newstepm is the new shorter stepm and stepm can be +expressed as a multiple of newstepm, like newstepm=n stepm, then the +following approximation holds: +

aij(stepm) = aij(n . stepm) - ln(n)
+
and +
bij(stepm) = bij(n . stepm) .
+ +

For example if you already ran for a 6 months interval and +got:
+ 

# Parameters
+12 -13.390179  0.126133 
+13  -7.493460  0.048069 
+21   0.575975 -0.041322 
+23  -4.748678  0.030626 
+
+If you now want to get the monthly estimates, you can guess the aij by +substracting ln(6)= 1,7917
and running
+
12 -15.18193847  0.126133 
+13 -9.285219469  0.048069
+21 -1.215784469 -0.041322
+23 -6.540437469  0.030626
+
+and get
+
12 -15.029768 0.124347 
+13 -8.472981 0.036599 
+21 -1.472527 -0.038394 
+23 -6.553602 0.029856 
+

+which is closer to the results. The approximation is probably useful
+only for very small intervals and we don't have enough experience to
+know if you will speed up the convergence or not.
+
         -ln(12)= -2.484
+ -ln(6/1)=-ln(6)= -1.791
+ -ln(3/1)=-ln(3)= -1.0986
+-ln(12/6)=-ln(2)= -0.693
+

+
 
Guess values for computing variances

 
 
This is an output if mle=1. But it can be