rankest.gpcr: Estimate number of principal components to retain for gpcr

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

Description

Estimate number of principal components to retain for gpcr

Usage

rankest.gpcr(
  formula,
  data,
  max.ncomp = NULL,
  family = gaussian(),
  crit = c("bic", "aic"),
  print = TRUE,
  plot = TRUE
)

Arguments

formula	model formula
data	data frame. should only contain numeric covariates!
max.ncomp	maximum number of components to try
family	a glm family. defaults to gaussian()
crit	one of "bic" or "aic". defaults to "bic" as the BIC tends to be more parsimonious than AIC.
print	should the results be printed to the console? defaults to TRUE.
plot	should the results be visualized in a plot? defaults to TRUE.

Value

invisibly returns an integer for the number of factors.

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