nFactors (version 2.3.3)

eigenComputes: 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

value

numeric: return a vector of eigenvalues

Examples

# NOT RUN {
# .......................................................
# 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")
# .......................................................
 
# }