BRLasso {elasso} R Documentation

## Bootstrap ranking LASSO model.

### Description

This function performs a LASSO logistic regression model using a bootstrap ranking procedure.

### Usage

BRLasso(x, y, B = 5, Boots = 100, kfold = 10)


### Arguments

 x the predictor matrix y the response variable, a factor object with values of 0 and 1 B the external loop for intersection operation, with the default value 5 Boots the internal loop for bootstrap sampling, with the default value 100 kfold the K-fold cross validation, with the default value 10

### References

Guo, P., Zeng, F., Hu, X., Zhang, D., Zhu, S., Deng, Y., & Hao, Y. (2015). Improved Variable Selection Algorithm Using a LASSO-Type Penalty, with an Application to Assessing Hepatitis B Infection Relevant Factors in Community Residents. PLoS One, 27;10(7):e0134151.

### Examples

library(datasets)
X <- as.matrix(subset(iris,iris$Species!="setosa")[,-5]) Y <- as.factor(ifelse(subset(iris,iris$Species!="setosa")[,5]=='versicolor',0,1))
BRLasso.fit$var.selected # Coefficients of the selected variables BRLasso.fit$var.coef