File jagmnl2.out is output from Gauss program jagmnl2.src Date is: 1998.0000 2.0000000 5.0000000 7678001.0 ------------------------------------------------------------------------------- Variable Mean Std Dev Variance Minimum Maximum Valid Missing ------------------------------------------------------------------------------- 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 0.0000 0.0000 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 0.0000 0.0000 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 3-CHOICE MULTINOMIAL LOGIT MAXIMUM LIKELIHOOD using Maxlik and ghmnl1.src Coefficients for choice 0 normalized to zero First set of coefficients for choice 1 Second set of coefficients for choice 2 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 D3NUMBID Parameters (Variables) names ONE REALREST BIDPREM SIZE ONE REALREST BIDPREM SIZE =============================================================================== MAXLIK Version 4.0.16 2/05/98 9:19 pm =============================================================================== Data Set: jaggiatr ------------------------------------------------------------------------------- return code = 0 normal convergence Mean log-likelihood 0.472737 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 0.4373 3.0117 0.145 0.4423 -0.0000 REALREST -2.1376 0.7792 -2.743 0.0030 -0.0000 BIDPREM 1.5192 2.1966 0.692 0.2446 -0.0000 SIZE 0.1625 0.1840 0.883 0.1886 -0.0000 ONE 3.7065 3.0856 1.201 0.1148 -0.0000 REALREST -2.1407 0.7628 -2.806 0.0025 -0.0000 BIDPREM -1.0872 2.2666 -0.480 0.3157 -0.0000 SIZE 0.2261 0.1863 1.214 0.1124 -0.0000 Correlation matrix of the parameters 1.000 -0.212 -0.984 -0.112 0.863 -0.202 -0.842 -0.105 -0.212 1.000 0.111 -0.150 -0.187 0.782 0.095 -0.126 -0.984 0.111 1.000 0.059 -0.850 0.106 0.859 0.055 -0.112 -0.150 0.059 1.000 -0.110 -0.090 0.060 0.941 0.863 -0.187 -0.850 -0.110 1.000 -0.199 -0.984 -0.114 -0.202 0.782 0.106 -0.090 -0.199 1.000 0.095 -0.110 -0.842 0.095 0.859 0.060 -0.984 0.095 1.000 0.061 -0.105 -0.126 0.055 0.941 -0.114 -0.110 0.061 1.000 Number of iterations 6 Minutes to convergence 0.00183