# Regularized Linear Models

## Documentation for package ‘mpath’ version 0.3-25

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

AIC.glmreg | Methods for mpath Objects
AIC.zipath | Methods for mpath Objects
be.zeroinfl | conduct backward stepwise variable elimination for zero inflated count regression
BIC.glmreg | Methods for mpath Objects
BIC.zipath | Methods for mpath Objects
breadReg | Bread for Sandwiches in Regularized Estimators
breadReg.zipath | Bread for Sandwiches in Regularized Estimators
coef.cv.glmreg | Cross-validation for glmreg
coef.cv.nclreg | Cross-validation for nclreg
coef.cv.zipath | Cross-validation for zipath
coef.glmreg | Model predictions based on a fitted "glmreg" object.
coef.zipath | Methods for zipath Objects
conv2glmreg | convert glm object to class glmreg
conv2zipath | convert zeroinfl object to class zipath
cv.glmreg | Cross-validation for glmreg
cv.glmreg.default | Cross-validation for glmreg
cv.glmreg.formula | Cross-validation for glmreg
cv.glmreg.matrix | Cross-validation for glmreg
cv.glmregNB | Cross-validation for glmregNB
cv.glmreg_fit | Internal function of cross-validation for glmreg
cv.nclreg | Cross-validation for nclreg
cv.nclreg.default | Cross-validation for nclreg
cv.nclreg.formula | Cross-validation for nclreg
cv.nclreg.matrix | Cross-validation for nclreg
cv.nclreg_fit | Internal function of cross-validation for nclreg
cv.zipath | Cross-validation for zipath
cv.zipath.default | Cross-validation for zipath
cv.zipath.formula | Cross-validation for zipath
cv.zipath.matrix | Cross-validation for zipath
cv.zipath_fit | Cross-validation for zipath
deviance.glmreg | fit a GLM with lasso (or elastic net), snet or mnet regularization
estfunReg | Extract Empirical First Derivative of Log-likelihood Function
estfunReg.zipath | Extract Empirical First Derivative of Log-likelihood Function
fitted.zipath | Methods for zipath Objects
glmreg | fit a GLM with lasso (or elastic net), snet or mnet regularization
glmreg.default | fit a GLM with lasso (or elastic net), snet or mnet regularization
glmreg.formula | fit a GLM with lasso (or elastic net), snet or mnet regularization
glmreg.matrix | fit a GLM with lasso (or elastic net), snet or mnet regularization
glmregNB | fit a negative binomial model with lasso (or elastic net), snet and mnet regularization
glmregNegbin | fit a negative binomial model with lasso (or elastic net), snet and mnet regularization
glmreg_fit | Internal function to fit a GLM with lasso (or elastic net), snet and mnet regularization
hessianReg | Hessian Matrix of Regularized Estimators
logLik.glmreg | fit a GLM with lasso (or elastic net), snet or mnet regularization
logLik.zipath | Methods for zipath Objects
meatReg | Meat Matrix Estimator
model.matrix.zipath | Methods for zipath Objects
ncl | fit a nonconvex loss based robust linear model
ncl.default | fit a nonconvex loss based robust linear model
ncl.formula | fit a nonconvex loss based robust linear model
ncl.matrix | fit a nonconvex loss based robust linear model
nclreg | fit a nonconvex loss based robust linear model with lasso (or elastic net), snet or mnet regularization
nclreg.default | fit a nonconvex loss based robust linear model with lasso (or elastic net), snet or mnet regularization
nclreg.formula | fit a nonconvex loss based robust linear model with lasso (or elastic net), snet or mnet regularization
nclreg.matrix | fit a nonconvex loss based robust linear model with lasso (or elastic net), snet or mnet regularization
nclreg_fit | Internal function to fit a nonconvex loss based robust linear model with lasso (or elastic net), snet and mnet regularization
ncl_fit | Internal function to fit a nonconvex loss based robust linear model
plot.cv.glmreg | Cross-validation for glmreg
plot.cv.nclreg | Cross-validation for nclreg
plot.glmreg | plot coefficients from a "glmreg" object
predict.cv.glmreg | Cross-validation for glmreg
predict.cv.zipath | Cross-validation for zipath
predict.glmreg | Model predictions based on a fitted "glmreg" object.
predict.zipath | Methods for zipath Objects
predprob.zipath | Methods for zipath Objects
print.summary.glmregNB | Summary Method Function for Objects of Class 'glmregNB'
print.summary.zipath | Methods for zipath Objects
pval.zipath | compute p-values from penalized zero-inflated model with multi-split data
residuals.zipath | Methods for zipath Objects
rzi | random number generation of zero-inflated count response
sandwichReg | Making Sandwiches with Bread and Meat for Regularized Estimators
se | Standard Error of Regularized Estimators
se.zipath | Standard Error of Regularized Estimators
stan | standardize variables
summary.glmregNB | Summary Method Function for Objects of Class 'glmregNB'
summary.zipath | Methods for zipath Objects
terms.zipath | Methods for zipath Objects
tuning.zipath | find optimal path for penalized zero-inflated model
zipath | Fit zero-inflated count data linear model with lasso (or elastic net), snet or mnet regularization
zipath.default | Fit zero-inflated count data linear model with lasso (or elastic net), snet or mnet regularization
zipath.formula | Fit zero-inflated count data linear model with lasso (or elastic net), snet or mnet regularization
zipath.matrix | Fit zero-inflated count data linear model with lasso (or elastic net), snet or mnet regularization
zipath_fit | Internal function to fit zero-inflated count data linear model with lasso (or elastic net), snet or mnet regularization