frq: Forward Regression Selection for Quantile Regression Models

In pboost: Profile Boosting Framework for Parametric Models

Forward Regression Selection for Quantile Regression Models

Description

frq() inherits the usage of the function quantreg::rq, and performs forward regression selection for quantile regression models.

Usage

frq(
  formula,
  tau = 0.5,
  data,
  subset,
  weights,
  na.action,
  method = "br",
  model = TRUE,
  contrasts = NULL,
  ...,
  selectFun = logLik,
  stopFun = "EBIC",
  keep = NULL,
  maxK = NULL,
  verbose = FALSE
)

frq.fit(
  x,
  y,
  tau = 0.5,
  method = "br",
  ...,
  selectFun = "logLik",
  stopFun = "EBIC",
  keep = NULL,
  maxK = NULL,
  verbose = FALSE
)

Arguments

formula	Parameter passed to quantreg::rq.
tau	Parameter passed to quantreg::rq.
data	Parameter passed to quantreg::rq.
subset	Parameter passed to quantreg::rq.
weights	Parameter passed to quantreg::rq.
na.action	Parameter passed to quantreg::rq.
method	Parameter passed to quantreg::rq.
model	Parameter passed to quantreg::rq.
contrasts	Parameter passed to quantreg::rq.
...	Parameters passed to quantreg::rq.
selectFun	Parameter passed to frs.
stopFun	Parameter passed to frs.
keep	Parameter passed to frs.
maxK	Parameter passed to frs.
verbose	Parameter passed to frs.
x	Parameter passed to quantreg::rq.fit.
y	Parameter passed to quantreg::rq.fit.

Value

A rq model object fitted on the selected features.

NULL

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