choice.component: choice.component

In martinparies/PCAOS: PCA.OS

choice.component

Description

Helps the user to choose the appropriate number of PCAOS component to optimize

Usage

choice.component(
  data,
  level.scale = rep("num", ncol(data)),
  nb.comp.to.investigate = 5,
  supp.var = NULL
)

Arguments

data	a data frame with n rows (individuals) and p columns (numeric, nominal and/or ordinal variables)
level.scale	vector(length p) giving the nature of each variable. Possible values: "nom", "ord", "num"
nb.comp.to.investigate	Number of components to investigate (default=ncol(data))
supp.var	a vector indicating the indexes of the supplementary variables

Value

Data frame with global Loss value and percentage of the quantified variables inertia explained, for different model dimensionality (H). The last column provides the variation in percentage between to two successive size of dimensionality.

Author(s)

• Martin PARIES (Maintainer: [e-mail])

• Evelyne Vigneau

• Stephanie Bougeard

Examples

data("antibiotic")

#Construction of the "level.scale" argument for this dataset
level.scale <- rep(NA,ncol(antibiotic))
level.scale[c(2,3,4)] <- "num"
level.scale[c(1,5,6,7,8,9,10,11,12,13,14,15)] <- "nom"
level.scale[c(1,15)] <- "ord"

res.choice <- choice.component(antibiotic,level.scale)
res.choice

martinparies/PCAOS documentation built on March 15, 2023, 7:19 a.m.