Learn R Programming

⚠️There's a newer version (0.4-2.26) of this package.Take me there.

mpath (version 0.1-20)

Regularized Linear Models

Description

Algorithms for fitting model-based penalized coefficient paths. Currently the models include penalized Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial regression models. The penalties include least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP), and each possibly combining with L_2 penalty.

Copy Link

Version

Install

install.packages('mpath')

Monthly Downloads

611

Version

0.1-20

License

GPL-2

Maintainer

Zhu Wang

Last Published

November 22nd, 2015

Functions in mpath (0.1-20)

cv.zipath

Cross-validation for zipath
mpath-internal

Internal mpath functions
breadReg

Bread for Sandwiches in Regularized Estimators
methods

Methods for mpath Objects
predict.zipath

Methods for zipath Objects
cv.glmreg

Cross-validation for glmreg
be.zeroinfl

conduct backward stepwise variable elimination for zero inflated count regression
tuning.zipath

find optimal penalized zero-inflated model
cv.glmregNB

Cross-validation for glmregNB
rzi

random number generation of zero-inflated count response
glmregNB

fit a negative binomial model with lasso (or elastic net), snet and mnet regularization
se

Standard Error of Regularized Estimators
glmreg_fit

Internal function to fit a GLM with lasso (or elastic net), snet and mnet regularization
meatReg

Meat Matrix Estimator
summary.glmregNB

Summary Method Function for Objects of Class 'glmregNB'
sandwichReg

Making Sandwiches with Bread and Meat for Regularized Estimators
hessianReg

Hessian Matrix of Regularized Estimators
estfunReg

Extract Empirical First Derivative of Log-likelihood Function
predict.glmreg

Model predictions based on a fitted "glmreg" object.
conv2zipath

convert zeroinfl object to class zipath
vuong.test

Vuong's non-nested hypothesis test
plot.glmreg

plot coefficients from a "glmreg" object
conv2glmreg

convert glm object to class glmreg
pval.zipath

compute p-values from penalized zero-inflated model with multi-split data
zipath

Fit zero-inflated count data linear model with lasso (or elastic net), snet or mnet regularization
cv.glmreg_fit

Internal function of cross-validation for glmreg
glmreg

fit a GLM with lasso (or elastic net), snet or mnet regularization