A B C D E F G H L M N P R S T U Z
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 |
breastfeed | Breast feeding decision |
ccglm | fit a CC-estimator for robust generalized linear models |
ccglm.formula | fit a CC-estimator for robust generalized linear models |
ccglmreg | Fit a penalized CC-estimator |
ccglmreg.default | Fit a penalized CC-estimator |
ccglmreg.formula | Fit a penalized CC-estimator |
ccglmreg.matrix | Fit a penalized CC-estimator |
ccglmreg_fit | Internal function for penalized CC-estimators |
ccsvm | fit case weighted support vector machines with robust loss functions |
ccsvm.default | fit case weighted support vector machines with robust loss functions |
ccsvm.formula | fit case weighted support vector machines with robust loss functions |
ccsvm.matrix | fit case weighted support vector machines with robust loss functions |
ccsvm_fit | Fit iteratively re-weighted support vector machines for robust loss functions |
coef.ccsvm | fit case weighted support vector machines with robust loss functions |
coef.cv.ccglmreg | Cross-validation for ccglmreg |
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 |
compute_g | Compute concave function values |
compute_wt | Weight value from concave function |
conv2glmreg | convert glm object to class glmreg |
conv2zipath | convert zeroinfl object to class zipath |
cv.ccglmreg | Cross-validation for ccglmreg |
cv.ccglmreg.default | Cross-validation for ccglmreg |
cv.ccglmreg.formula | Cross-validation for ccglmreg |
cv.ccglmreg.matrix | Cross-validation for ccglmreg |
cv.ccglmreg_fit | Internal function of cross-validation for ccglmreg |
cv.ccsvm | Cross-validation for ccsvm |
cv.ccsvm.default | Cross-validation for ccsvm |
cv.ccsvm.formula | Cross-validation for ccsvm |
cv.ccsvm.matrix | Cross-validation for ccsvm |
cv.ccsvm_fit | Internal function of cross-validation for ccsvm |
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 |
docvisits | Doctor visits |
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 |
gfunc | Convert response value to raw prediction in GLM |
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 |
loss2 | Composite Loss Value |
loss2_ccsvm | Composite Loss Value for epsilon-insensitive Type |
loss3 | Composite Loss Value for GLM |
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 | Optimize a nonconvex loss with regularization |
nclreg.default | Optimize a nonconvex loss with regularization |
nclreg.formula | Optimize a nonconvex loss with regularization |
nclreg.matrix | Optimize a nonconvex loss with regularization |
nclreg_fit | Internal function to fitting a nonconvex loss based robust linear model with regularization |
ncl_fit | Internal function to fit a nonconvex loss based robust linear model |
plot.cv.ccglmreg | Cross-validation for ccglmreg |
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 |
update_wt | Compute weight value |
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 |