eigenComputes {nFactors}

Computes Eigenvalues According to the Data Type

Description

The eigenComputes function computes eigenvalues from the identified data type. It is used internally in many fonctions of the nFactors package in order to apply these to a vector of eigenvalues, a matrix of correlations or covariance or a data frame.

Usage

eigenComputes(x, cor = TRUE, model = "components", ...)

Arguments

x

numeric: a vector of eigenvalues, a matrix of correlations or of covariances or a data.frame of data

cor

logical: if TRUE computes eigenvalues from a correlation matrix, else from a covariance matrix

model

character: "components" or "factors"

...

variable: additionnal parameters to give to the cor or cov functions

Value

numeric: return a vector of eigenvalues

Author(s)

Gilles Raiche
Centre sur les Applications des Modeles de Reponses aux Items (CAMRI)
Universite du Quebec a Montreal
[e-mail]

David Magis
Departement de mathematiques
Universite de Liege
[e-mail]

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")
# .......................................................