Synthetic dataset with binary response
compute C index for a Cox model
Synthetic dataset with right-censored survival response
Synthetic dataset with multiple Gaussian responses
Synthetic dataset with multinomial response
Synthetic dataset with count response
Synthetic dataset with Gaussian response
Synthetic dataset with sparse design matrix
assess performance of a 'glmnet' object using test data.
Simulated data for the glmnet vignette
fit a glm with all the options in 'glmnet'
Fit a Cox regression model with elastic net regularization for a single value of lambda
Fit a Cox regression model with elastic net regularization for a path of lambda values
Elastic net objective function value for Cox regression model
Compute gradient for Cox model
Compute deviance for Cox model
Cross-validation for glmnet
Elastic net deviance value
Extract the deviance from a glmnet object
Solve weighted least squares (WLS) problem for a single lambda value
Helper function for Cox deviance and gradient
Get lambda max for Cox regression model
Helper function to get etas (linear predictions)
Get null deviance, starting mu and lambda max
Internal glmnet functions
Elastic net model paths for some generalized linear models
fit a GLM with lasso or elasticnet regularization
internal glmnet parameters
Fit a GLM with elastic net regularization for a single value of lambda
Display the names of the measures used in CV for different "glmnet" families
Fit a GLM with elastic net regularization for a path of lambda values
convert a data frame to a data matrix with one-hot encoding
Helper function to fit coxph model for survfit.coxnet
Helper function to amend ... for new data in survfit.coxnet
Replace the missing entries in a matrix columnwise with the entries in a supplied vector
Elastic net objective function value
Elastic net penalty value
plot the cross-validation curve produced by cv.glmnet
plot coefficients from a "glmnet" object
make predictions from a "cv.glmnet" object.
Extract coefficients from a glmnet object
Get predictions from a 'glmnetfit' fit object
print a cross-validated glmnet object
print a glmnet object
Make response for coxnet
Generate multinomial samples from a probability matrix
Add strata to a Surv object
Compute a survival curve from a coxnet object
Compute a survival curve from a cv.glmnet object
Check if glmnet should call cox.path
Helper function to compute weighted mean and standard deviation