Transformations of the Explanatory Variables in the Logistic Regression Model for Binary Data
研究了通过变换解释变量来改善二分类数据逻辑回归模型拟合的方法，基于结果组条件分布的对数密度比函数，对计量经济学和统计建模有用。
Some results are presented on improving the fit of the logistic regression model for binary data by transforming the vector of explanatory variables. The methods are based on consideration of the distributions of these variables conditional on outcome group. The transformations required are the functions of the explanatory variables which appear in the log density ratio of the conditional distributions.