Return to biaspar.imach CVS log

Up to [Local Repository] / imach / html / doc

Annotation of imach/html/doc/biaspar.imach, revision 1.7

1.7     ! brouard     1: #0.99r24
1.6       brouard     2: #Number of iterations & function calls = 33 & 6007, -2 Log likelihood = 46617.105944307616
                      3: title=1st_example datafile=data1.txt lastobs=8600 firstpass=1 lastpass=4
                      4: ftol=1.000000e-08 stepm=1 ncovcol=2 nqv=0 ntv=0 nqtv=0 nlstate=2 ndeath=1 maxwav=4 mle= 1 weight=0
                      5: model=1+age+.
                      6: # Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...
                      7: 12  -12.3175753    0.0931122 
                      8: 13  -10.1631670    0.0548384 
                      9: 21   -1.6685685   -0.0339056 
                     10: 23   -5.6869201    0.0181350 
                     11: # Scales (for hessian or gradient estimation)
                     12: 12 2.00000e-04 2.00000e-06
                     13: 13 3.00000e-04 4.00000e-06
                     14: 21 1.00000e-04 1.00000e-06
                     15: 23 3.00000e-04 3.00000e-06
                     16: # Covariance matrix 
                     17: # 121 Var(a12)
                     18: # 122 Cov(b12,a12) Var(b12)
                     19: #   ...
                     20: # 232 Cov(b23,a12)  Cov(b23,b12) ... Var (b23)
                     21: #121 Var(a12)
                     22: #122 Cov(b12,a12) Var(b12)
                     23: #131 Cov(a13,a12) Cov(a13,b12) Var(a13)
                     24: #132 Cov(b13,a12) Cov(b13,b12) Cov(b13,a13) Var(b13)
                     25: #211 Cov(a21,a12) Cov(a21,b12) Cov(a21,a13) Cov(a21,b13) Var(a21)
                     26: #212 Cov(b21,a12) Cov(b21,b12) Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)
                     27: #231 Cov(a23,a12) Cov(a23,b12) Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)
                     28: #232 Cov(b23,a12) Cov(b23,b12) Cov(b23,a13) Cov(b23,b13) Cov(b23,a21) Cov(b23,b21) Cov(b23,a23) Var(b23)
                     29: 121 1.0846319e-01
                     30: 122 -1.30062e-03 1.5689741e-05
                     31: 131 -5.39098e-02 6.59806e-04 3.0197746e-01
                     32: 132 6.43147e-04 -7.94760e-06 -3.73264e-03 4.6435109e-05
                     33: 211 7.75092e-02 -9.24613e-04 1.91004e-02 -2.45003e-04 4.7111318e-01
                     34: 212 -9.24119e-04 1.10769e-05 -2.40929e-04 3.09854e-06 -5.60404e-03 6.7019135e-05
                     35: 231 4.86258e-02 -5.50028e-04 -9.42536e-02 1.06700e-03 -2.57577e-03 2.94283e-05 2.5010261e-01
                     36: 232 -5.52529e-04 6.29410e-06 1.11646e-03 -1.27952e-05 3.55428e-05 -4.16204e-07 -2.83674e-03 3.2358065e-05
                     37: # agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).
                     38: agemin=70 agemax=95 bage=70 fage=95 estepm=1 ftolpl=6.000000e-04
                     39: begin-prev-date=1/1/1984 end-prev-date=1/6/1988 mov_average=0
                     40: pop_based=1
                     41: prevforecast=1 starting-proj-date=1/1/1989 final-proj-date=1/1/2000 mobil_average=0
                     42: #backcast=1 starting-back-date=1/1/1990 final-back-date=1/1/1970 mobil_average=1
1.5       brouard    43: # Results model=1+age.
1.6       brouard    44: result: .