eigenComputes {nFactors} | R Documentation |
Computes Eigenvalues According to the Data Type
Description
The eigenComputes
function computes eigenvalues from the identified data
type. The function is used internally in many
fonctions of the nFactors package to be able 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
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
raiche.gilles@uqam.ca, http://www.er.uqam.ca/nobel/r17165/
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")
# From a covariance matrix
x3 <- cov(x2)
eigenComputes(x3, cor=TRUE, use="everything")
eigenComputes(x3, cor=FALSE, use="everything")
# From a correlation matrix
x4 <- cor(x2)
eigenComputes(x4, use="everything")
# .......................................................
[Package
nFactors version 2.3.1
Index]