logit模型,logit回归

我试图为德国信用数据(www4.stat.ncsu.edu/~boos/var.select/german.credit.html)运行logit回归。为了测试代码，我只使用了数值变量，并尝试用下面的代码对结果进行回归。当我检查数据logit回归和Python中的奇异矩阵错误

import pandas as pd

import statsmodels.api as sm

import pylab as pl

import numpy as np

df = pd.read_csv("germandata.txt",delimiter=' ')

df.columns = ["chk_acc","duration","history","purpose","amount","savings_acc","employ_since","install_rate","pers_status","debtors","residence_since","property","age","other_plans","housing","existing_credit","job","no_people_liab","telephone","foreign_worker","admit"]

#pls note that I am only retaining numeric variables

cols_to_keep = ['admit','duration', 'amount', 'install_rate','residence_since','age','existing_credit','no_people_liab']

# rank of cols_to_keep is 8

print np.linalg.matrix_rank(df[cols_to_keep].values)

data = df[cols_to_keep]

data['intercept'] = 1.0

train_cols = data.columns[1:]

#to check the rank of train_cols, which in this case is 8

print np.linalg.matrix_rank(data[train_cols].values)

#fit logit model

logit = sm.Logit(data['admit'], data[train_cols])

result = logit.fit()

所有8.0列似乎无关。尽管如此，我得到了奇异矩阵错误。你能帮忙吗？

由于