pec_cv: k-fold cross validated prediction error curve (pec)

In adibender/pamm: Functions and Utilities for fitting Piece-wise Exponential (Additive) models

Description

k-fold cross validated prediction error curve (pec)

Usage

pec_cv(data, formula_pam, formula_ped = Surv(time, status) ~ ., k = 10L,
  formula_ipcw = Surv(time, status) ~ 1, cut = NULL, method = pamm, ...)

Arguments

data	The data in standard time-to-event data format which can be tansformed in PED (see split_data).
formula_pam	The formula used to fit the PAM (see pam).
formula_ped	The formula used to transform data to PED (see split_data).
k	The number of folds to be used in cross-validation.
formula_ipcw	The formula used to calculate inverse probability censoring weights (IPCW). See ipcw for details.
cut	the vector of timepoints to cut at
method	The function to which formula_pam will be passed to fit the model in the k-th fold.
...	Further arguments passed to split_data.

See Also

pec, ipcw

adibender/pamm documentation built on May 14, 2019, 5:22 p.m.