test

<p>The output of WLogit in the example given in the vignette.</p>

datasets

It proposes a novel variable selection approach in classification problem that takes into account the correlations that may exist between the predictors of the design matrix in a high-dimensional logistic model. Our approach consists in rewriting the initial high-dimensional logistic model to remove the correlation between the predictors and in applying the generalized Lasso criterion.

Wencan Zhu

WLogit

Variable Selection in High-Dimensional Logistic Regression
Models using a Whitening Approach

test function

<p>The format is:
List of 4
 $ beta          : num [1:50, 1:500] 0 0 0 0 0 ...
 $ lambda        : num [1:50] 100.8 80 73 58.9 56.7 ...
 $ beta.min      : num [1:500] 0.0194 0.0348 0.0259 0.0287 0.0385 ...
 $ log.likelihood: num [1:50] 57.7 57.7 57.7 57.7 57.7 ...</p>

test: WLogit output

Description

Usage

Arguments

Format

Examples