gpcr.boot: Bootstrap Generalized Principal Components Regression...

In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities

Description

This function provides a means of obtaining bias corrected and accelerated bootstrap confidence intervals for the regression coefficients (reflecting the original full set of predictors) as well as exact empirical p-values.

Usage

gpcr.boot(
  formula,
  data,
  ncomp = NULL,
  family = gaussian(),
  nsamp = 1000,
  parallel = T,
  ncores = 4,
  conf.level = 0.95
)

Arguments

formula	a model formula
data	a data frame
ncomp	The number of principal components to retain. If left as NULL the minimum of P-1 and the number of non-zero eigenvalues will be returned.
family	one of the glm families supported by R's glm function.
nsamp	number of bootstrap samples
parallel	whether to use parallel processing for bootstrapping
ncores	if parallel=TRUE, the number of cores. defaults to 4.
conf.level	the confidence level for the confidence intervals. defaults to 0.95

Value

an object with class "gpcrBoot".

abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.