foehnix_glmnet: Wrapper Function Around glmnet Logistic Regression

In retostauffer/Rfoehnix: Objective Foehn Diagnosis

Wrapper Function Around glmnet Logistic Regression

Description

The foehnix function allows to estimate a regularized logistic regression model for the concomitants. In case glmnet.control is provided the EM algorithm uses this function to estimate the regression coefficients of the concomitant model. glmnet.control allows to specify options forwarded to glmnet::glmnet except family ("binomial") and intercept (TRUE). Depending on glmnet.control the AIC, BIC, or log-likelihood criterion will be used.

Usage

foehnix_glmnet(y, x, arg)

Arguments

y	response vector (binary)
x	design matrix. If a column "(Intercept)" exists it will be dropped (as we force glmnet to estimate an intercept).
arg	list of arguments forwarded to glmnet::glmnet.

Value

Returns an object of class ccmodel for foehnix models.

Author(s)

Reto Stauffer

retostauffer/Rfoehnix documentation built on June 5, 2023, 11:39 p.m.