蓝色 发表于 2015-4-8 17:05 
1。既然结果里面有,那就拷贝出来用就可以;
2、biprobit postestimation里面有相关的wald检验的命令
您好 我想请教一下 biprobit 里面的自变量有什么要求吗?我的因变量大部分都是虚拟变量,请问符合吗?还有我做出来的为什么吗一直在迭代? log likelihood = -<inf> (could not be evaluated)
feasible: log likelihood = -75.957163
rescale: log likelihood = -33.598727
rescale eq: log likelihood = -33.598727
Iteration 0: log likelihood = -33.598727
Iteration 1: log likelihood = -21.902964 (not concave)
Iteration 2: log likelihood = -21.523673 (not concave)
Iteration 3: log likelihood = -21.233643 (not concave)
Iteration 4: log likelihood = -20.880196 (not concave)
Iteration 5: log likelihood = -20.725274 (not concave)
Iteration 6: log likelihood = -20.609077 (not concave)
Iteration 7: log likelihood = -20.535909 (not concave)
Iteration 8: log likelihood = -20.489329 (not concave)
Iteration 9: log likelihood = -20.448094 (not concave)
Iteration 10: log likelihood = -20.370909
Iteration 11: log likelihood = -20.020702 (backed up)
Iteration 12: log likelihood = -19.747352
Iteration 13: log likelihood = -19.66007
Iteration 14: log likelihood = -19.655925
Iteration 15: log likelihood = -19.636534 (not concave)
Iteration 16: log likelihood = -19.619722 (not concave)
Iteration 17: log likelihood = -19.617931 (not concave)
Iteration 18: log likelihood = -19.616719 (not concave)
Iteration 19: log likelihood = -19.615587 (not concave)
Iteration 20: log likelihood = -19.612931 (not concave)
Iteration 21: log likelihood = -19.60929 (not concave)
Iteration 22: log likelihood = -19.608357 (not concave)
Iteration 23: log likelihood = -19.607495 (not concave)
Iteration 24: log likelihood = -19.606634 (not concave)
然后下面这个是我的部分数据。
Age Sex Education Train Land Time Rcrop Agri_expend inCollate Ptcredit
4 0 2 0 200 1 27 20 1 1
3 0 2 0 500 1 65 38 1 1
3 0 2 0 200 2 26 12 1 1
3 0 1 0 150 3 19 8.5 1 1
3 0 1 0 400 1 52 27 1 1
3 0 1 0 350 1 45 28 1 1
4 0 1 0 500 1 70 42 1 1
3 0 2 0 120 0 6 2 1 0
4 0 1 0 260 1 33 18 1 1
4 1 2 0 180 1 23 11 1 1
2 0 1 1 230 2 29 14 1 1
我是一个刚刚接触stata的,希望可以得到您的帮助,麻烦了!