eigenComputes function

Computes Eigenvalues According to the Data Type

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.

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

Returns

numeric: return a vector of eigenvalues

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(s)

Gilles Raiche

Centre sur les Applications des Modeles de Reponses aux Items (CAMRI)

Universite du Quebec a Montreal

raiche.gilles@uqam.ca

David Magis

Departement de mathematiques

Universite de Liege

David.Magis@ulg.ac.be