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

Value

A coxph model object fitted on the selected features.

Examples

library(survival)
set.seed(2026)
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)
fcoxph(Surv(time, status) ~ ., DF, verbose=TRUE)

pboost documentation built on May 24, 2026, 9:08 a.m.