zhangtao 发表于 2012-11-5 20:51 
(0) : error G0008 : '#include seldata.src' : Syntax error
(0) : error G0008 : '#include ghmnl.sr ...
设定好Working Directory,然后执行jagmnl1.prg
Date is:
2012.0000
11.000000
6.0000000
3672966.6
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Variable Mean Std Dev Variance Minimum Maximum Valid Missing
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DOCNO 82174.4127 2251.78345070528.564378001.000085059.0000 126 0
WEEKS 11.4490 7.7114 59.4661 2.8570 41.4290 126 0
NUMBIDS 1.7381 1.4321 2.0509 0.0000 10.0000 126 0
TAKEOVER 1.0000 ----- ----- 1.0000 1.0000 126 0
BIDPREM 1.3468 0.1893 0.0358 0.9427 2.0664 126 0
INSTHOLD 0.2518 0.1856 0.0345 0.0000 0.9040 126 0
SIZE 1.2190 3.0966 9.5891 0.0177 22.1690 126 0
LEGLREST 0.4286 0.4968 0.2469 0.0000 1.0000 126 0
REALREST 0.1825 0.3878 0.1504 0.0000 1.0000 126 0
FINREST 0.1032 0.3054 0.0933 0.0000 1.0000 126 0
REGULATN 0.2698 0.4456 0.1986 0.0000 1.0000 126 0
WHTKNGHT 0.5952 0.4928 0.2429 0.0000 1.0000 126 0
ONE 1.0000 ----- ----- 1.0000 1.0000 126 0
SIZESQ 10.9990 59.9148 3589.7819 0.0003 491.4646 126 0
D2NUMBID 0.9286 0.2586 0.0669 0.0000 1.0000 126 0
D3NUMBID 1.3571 0.6127 0.3754 0.0000 2.0000 126 0
BINARY LOGIT MAXIMUM LIKELIHOOD using Maxlik and ghmnl1.src
Dataset jaggiatr
Nr of observations 126.00000
Nr of times data is read 1.0000000
Nr of obs. read last chew 126.00000
Dependent variable D2NUMBID
Parameters (Variables) names
ONE REALREST BIDPREM SIZE
===============================================================================
MAXLIK Version 5.0.9 11/06/2012 10:12 am
===============================================================================
Data Set: jaggiatr
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return code = 0
normal convergence
Mean log-likelihood 0.877838
Number of cases 126
Covariance matrix of the parameters computed by the following method:
QML covariance matrix
Parameters Estimates Std. err. Est./s.e. Prob. Gradient
------------------------------------------------------------------
ONE 2.5688 2.7899 0.921 0.3572 0.0000
REALREST -2.1507 0.7279 -2.955 0.0031 0.0000
BIDPREM 0.3879 2.0280 0.191 0.8483 0.0000
SIZE 0.1938 0.1816 1.067 0.2858 0.0000
Correlation matrix of the parameters
1.000 -0.230 -0.982 -0.137
-0.230 1.000 0.116 -0.119
-0.982 0.116 1.000 0.080
-0.137 -0.119 0.080 1.000
Number of iterations 6
Minutes to convergence 0.00000