be_zeroinfl: conduct backward stepwise variable elimination for zero...

In mpath: Regularized Linear Models

conduct backward stepwise variable elimination for zero inflated count regression

Description

conduct backward stepwise variable elimination for zero inflated count regression from zeroinfl function

Usage

be.zeroinfl(object, data, dist=c("poisson", "negbin", "geometric"), alpha=0.05, 
            trace=FALSE)

Arguments

object	an object from function zeroinfl
data	argument controlling formula processing via model.frame.
dist	one of the distributions in zeroinfl function
alpha	significance level of variable elimination
trace	logical value, if TRUE, print detailed calculation results

Details

conduct backward stepwise variable elimination for zero inflated count regression from zeroinfl function

Value

an object of zeroinfl with all variables having p-values less than the significance level alpha

Author(s)

Zhu Wang <[e-mail]>

References

Zhu Wang, Shuangge Ma, Ching-Yun Wang, Michael Zappitelli, Prasad Devarajan and Chirag R. Parikh (2014) EM for Regularized Zero Inflated Regression Models with Applications to Postoperative Morbidity after Cardiac Surgery in Children, Statistics in Medicine. 33(29):5192-208.

Zhu Wang, Shuangge Ma and Ching-Yun Wang (2015) Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany, Biometrical Journal. 57(5):867-84.

mpath documentation built on Jan. 7, 2023, 1:17 a.m.