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https://github.com/cran/nFactors
24 October 2022, 04:44:14 UTC
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  • eigenComputes.rd
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Tip revision: d698320a894fbd444a99aa3d4dbce1f129cb82ac authored by Gilles Raiche on 28 March 2020, 04:50:06 UTC
version 2.4.1
Tip revision: d698320
eigenComputes.rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/eigenComputes.r
\name{eigenComputes}
\alias{eigenComputes}
\title{Computes Eigenvalues According to the Data Type}
\usage{
eigenComputes(x, cor = TRUE, model = "components", ...)
}
\arguments{
\item{x}{numeric: a \code{vector} of eigenvalues, a \code{matrix} of
correlations or of covariances or a \code{data.frame} of data}

\item{cor}{logical: if \code{TRUE} computes eigenvalues from a correlation
matrix, else from a covariance matrix}

\item{model}{character: \code{"components"} or \code{"factors"}}

\item{...}{variable: additionnal parameters to give to the \code{cor} or
\code{cov} functions}
}
\value{
numeric: return a vector of eigenvalues
}
\description{
The \code{eigenComputes} function computes eigenvalues from the identified data
type. It is used internally in many
fonctions of the \pkg{nFactors} package in order to apply these to a vector of
eigenvalues, a matrix of correlations or covariance or a data frame.
}
\examples{
# .......................................................
# Different data types
# Vector of eigenvalues
data(dFactors)
x1 <- dFactors$Cliff1$eigenvalues
eigenComputes(x1)

# Data from a data.frame
x2 <- data.frame(matrix(20*rnorm(100), ncol=5))
eigenComputes(x2, cor=TRUE,  use="everything")
eigenComputes(x2, cor=FALSE, use="everything")
eigenComputes(x2, cor=TRUE,  use="everything", method="spearman")
eigenComputes(x2, cor=TRUE,  use="everything", method="kendall")

x3 <- cov(x2)
eigenComputes(x3, cor=TRUE,  use="everything")
eigenComputes(x3, cor=FALSE, use="everything")

x4 <- cor(x2)
eigenComputes(x4, use="everything")
# .......................................................

}
\author{
Gilles Raiche \cr Centre sur les Applications des Modeles de
Reponses aux Items (CAMRI) \cr Universite du Quebec a Montreal\cr
\email{raiche.gilles@uqam.ca}
\cr \cr David Magis \cr Departement de mathematiques \cr Universite de Liege
\cr \email{David.Magis@ulg.ac.be}
}
\keyword{multivariate}

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