ic_exhaustive: Exhaustive Information Criteria for PLS Path Models

In semPLSModelSelection: Structural Equation Modeling Using Partial Least Squares

Description

The function computes a variety of information criteria for exhaustive PLS path models.

Usage

ic_exhaustive(object, LV, criteria, ...)

## S3 method for class 'sempls'
ic_exhaustive(object, LV, criteria, ...)

## S3 method for class 'ic_exhaustive'
print(x, minlength, digits, ...)

Arguments

object	an object of class sempls
LV	the focal component (latent variable)
criteria	A character vector naming the information criteria to calculate, see details.
x	object of class ic_exhaustive
minlength	the minimum length of the abbreviations
digits	specifies the minimum number of significant digits to be printed in values, see print.default
...	Arguments to pass down to other methods.

Value

ic	A numeric matrix containing the information criteria in the columns and models in the rows with respect to the focal component (latent variable).
all_fits	A list of all fitted models resulting from an exhaustive search for the focal component (latent variable)

See Also

ic, sempls

Examples

library("semPLS")
data(ECSImobi)
ecsi <- sempls(ECSImobi, mobi, wscheme="centroid")

### ic - information criteria
## All criteria for 'all' models
ic_exhaustive(ecsi, LV = "Satisfaction")

semPLSModelSelection documentation built on May 2, 2019, 5:28 p.m.