pcoxph: Profile Boosting for Cox proportional hazards Model

In pboost: Profile Boosting Framework for Parametric Models

Profile Boosting for Cox proportional hazards Model

Description

Profile boosting for Cox model.

Usage

pcoxph(
  formula,
  data,
  weights,
  subset,
  na.action,
  init,
  control,
  ties = c("efron", "breslow", "exact"),
  singular.ok = TRUE,
  robust,
  model = FALSE,
  x = FALSE,
  y = TRUE,
  tt,
  method = ties,
  id,
  cluster,
  istate,
  statedata,
  nocenter = c(-1, 0, 1),
  ...,
  stopFun = EBIC,
  keep = NULL,
  maxK = NULL,
  verbose = FALSE
)

Arguments

formula	See pboost.
data	See pboost.
weights	Parameters passed to survival::coxph.
subset	Parameters passed to survival::coxph.
na.action	Parameters passed to survival::coxph.
init	Parameters passed to survival::coxph.
control	Parameters passed to survival::coxph.
ties	Parameters passed to survival::coxph.
singular.ok	Parameters passed to survival::coxph.
robust	Parameters passed to survival::coxph.
model	Parameters passed to survival::coxph.
x	Parameters passed to survival::coxph.
y	Parameters passed to survival::coxph.
tt	Parameters passed to survival::coxph.
method	Parameters passed to survival::coxph.
id	Parameters passed to survival::coxph.
cluster	Parameters passed to survival::coxph.
istate	Parameters passed to survival::coxph.
statedata	Parameters passed to survival::coxph.
nocenter	Parameters passed to survival::coxph.
...	Parameters passed to survival::coxph.
stopFun	Parameters passed to pboost.
keep	Parameters passed to pboost.
maxK	Parameters passed to pboost.
verbose	Parameters passed to pboost.

Value

An coxph model object fitted on the selected features.

Examples

library(survival)
set.seed(2025)
n <- 300
p <- 200

DF <- data.frame(
    time = rpois(n, 5),
    status = rbinom(n, 1, 0.3),
    matrix(rnorm(n*p), n)
)

pcoxph(Surv(time, status) ~ ., DF, verbose=TRUE)

pboost documentation built on Jan. 9, 2026, 1:07 a.m.