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]