pec_pamm: Fit PAM to train data and calculate PEC on test data

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

Description

Fit PAM to train data and calculate PEC on test data

Usage

pec_pamm(data, idx_train, idx_test, formula_ped, formula_pam,
  formula_ipcw = Surv(time, status) ~ 1, times = NULL, cut = NULL,
  n = 50L, ...)

Arguments

data	The data in standard time-to-event data format which can be tansformed in PED (see split_data).
idx_train	Index of rows that indicate training set.
idx_test	Index of rows that indicate test set.
formula_ped	The formula used to transform data to PED (see split_data).
formula_pam	The formula used to fit the PAM (see pam).
formula_ipcw	The formula used to calculate inverse probability censoring weights (IPCW). See ipcw for details.
times	The time points at which prediction error will be evaluated
cut	the vector of timepoints to cut at
n	If times argument not specified, will create a sequence from minimal to maximal time of this length.
...	further arguments passed to split_data.

See Also

pec, ipcw

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