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http://dx.doi.org/10.5351/CKSS.2012.19.1.001

Variable Selection with Log-Density in Logistic Regression Model  

Kahng, Myung-Wook (Department of Statistics, Sookmyung Women's University)
Shin, Eun-Young (Department of Statistics, Sookmyung Women's University)
Publication Information
Communications for Statistical Applications and Methods / v.19, no.1, 2012 , pp. 1-11 More about this Journal
Abstract
We present methods to study the log-density ratio of the conditional densities of the predictors given the response variable in the logistic regression model. This allows us to select which predictors are needed and how they should be included in the model. If the conditional distributions are skewed, the distributions can be considered as gamma distributions. A simulation study shows that the linear and log terms are required in general. If the conditional distributions of xjy for the two groups overlap significantly, we need both the linear and log terms; however, only the linear or log term is needed in the model if they are well separated.
Keywords
Binary response variable; inverse regression; Kullback-Leibler divergence; log-density ratio; logistic regression;
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