GLMnet: Fitting GLMnet for use with predictRisk

In riskRegression: Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks

Fitting GLMnet for use with predictRisk

Description

Fit GLMnet models via a formula and a data set for use with predictRisk.

Usage

GLMnet(
  formula,
  data,
  lambda = NULL,
  cv = TRUE,
  alpha = 1,
  nfolds = 10,
  type.measure = "deviance",
  family,
  ...
)

Arguments

formula	A formula.
data	The data on which to fit the model.
lambda	The tuning parameters for GLMnet. If set to NULL, then it the parameters are chosen for you.
cv	Whether to use cross-validation or not. Default is TRUE.
alpha	The elasticnet mixing parameter. See the ?glmnet for more details.
nfolds	Number of folds for cross-validation. Default is 10.
type.measure	loss to use for cross-validation. Default is deviance.
family	passed to glmnet. Defaults for binary outcome to "binomial" and for survival to "cox".
...	Additional arguments that are passed on to the glmnet.

riskRegression documentation built on May 29, 2024, 10:59 a.m.