glmnet-package | Elastic net model paths for some generalized linear models |
assess.glmnet | assess performance of a 'glmnet' object using test data. |
beta_CVX | Simulated data for the glmnet vignette |
bigGlm | fit a glm with all the options in 'glmnet' |
Cindex | compute C index for a Cox model |
coef.cv.glmnet | make predictions from a "cv.glmnet" object. |
coef.cv.relaxed | make predictions from a "cv.glmnet" object. |
coef.glmnet | Extract coefficients from a glmnet object |
coef.relaxed | Extract coefficients from a glmnet object |
confusion.glmnet | assess performance of a 'glmnet' object using test data. |
coxgrad | compute gradient for cox model |
coxnet.deviance | compute deviance for cox model output |
cv.glmnet | Cross-validation for glmnet |
deviance.glmnet | Extract the deviance from a glmnet object |
dev_function | Elastic net deviance value |
elnet.fit | Solve weighted least squares (WLS) problem for a single lambda value |
get_eta | Helper function to get etas (linear predictions) |
get_start | Get null deviance, starting mu and lambda max |
glmnet | fit a GLM with lasso or elasticnet regularization |
glmnet.control | internal glmnet parameters |
glmnet.fit | Fit a GLM with elastic net regularization for a single value of lambda |
glmnet.measures | Display the names of the measures used in CV for different "glmnet" families |
glmnet.path | Fit a GLM with elastic net regularization for a path of lambda values |
makeX | convert a data frame to a data matrix with one-hot encoding |
na.replace | Replace the missing entries in a matrix columnwise with the entries in a supplied vector |
obj_function | Elastic net objective function value |
pen_function | Elastic net penalty value |
plot.cv.glmnet | plot the cross-validation curve produced by cv.glmnet |
plot.cv.relaxed | plot the cross-validation curve produced by cv.glmnet |
plot.glmnet | plot coefficients from a "glmnet" object |
plot.mrelnet | plot coefficients from a "glmnet" object |
plot.multnet | plot coefficients from a "glmnet" object |
plot.relaxed | plot coefficients from a "glmnet" object |
predict.coxnet | Extract coefficients from a glmnet object |
predict.cv.glmnet | make predictions from a "cv.glmnet" object. |
predict.cv.relaxed | make predictions from a "cv.glmnet" object. |
predict.elnet | Extract coefficients from a glmnet object |
predict.fishnet | Extract coefficients from a glmnet object |
predict.glmnet | Extract coefficients from a glmnet object |
predict.glmnetfit | Get predictions from a 'glmnetfit' fit object |
predict.lognet | Extract coefficients from a glmnet object |
predict.mrelnet | Extract coefficients from a glmnet object |
predict.multnet | Extract coefficients from a glmnet object |
predict.relaxed | Extract coefficients from a glmnet object |
print.bigGlm | print a glmnet object |
print.cv.glmnet | print a cross-validated glmnet object |
print.cv.relaxed | print a cross-validated glmnet object |
print.glmnet | print a glmnet object |
print.relaxed | print a glmnet object |
relax.glmnet | fit a GLM with lasso or elasticnet regularization |
rmult | Generate multinomial samples from a probability matrix |
roc.glmnet | assess performance of a 'glmnet' object using test data. |
x | Simulated data for the glmnet vignette |
y | Simulated data for the glmnet vignette |