loss_fn: Calculate the Log-Partial Likelihood for a Stratified Cox...

In survkl: Estimate Survival Data with Data Integration

Calculate the Log-Partial Likelihood for a Stratified Cox Model

Description

Computes the stratified Cox partial log-likelihood for given covariates, event indicators, times, and coefficients.

Usage

loss_fn(z, delta, time, stratum, beta)

Arguments

z	A numeric matrix (or data frame coercible to matrix) of covariates. Each row is an observation and each column a predictor.
delta	A numeric vector of event indicators (1 = event, 0 = censored).
time	A numeric vector of observed times (event or censoring).
stratum	An optional vector specifying the stratum for each observation (factor/character/numeric). If missing, a single-stratum model is assumed.
beta	A numeric vector of regression coefficients with length equal to the number of columns in z.

Details

Inputs are internally sorted by stratum and time. The function evaluates the stratified Cox partial log-likelihood using the supplied z, delta, beta, and the stratum sizes.

Value

A single numeric value giving the stratified Cox partial log-likelihood.

survkl documentation built on April 22, 2026, 1:08 a.m.