View source: R/eigenComputes.r
eigenComputes | R Documentation |
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", ...)
x |
numeric: a |
cor |
logical: if |
model |
character: |
... |
variable: additionnal parameters to give to the |
numeric: return a vector of eigenvalues
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
# ....................................................... # 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") # .......................................................
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