eigenFrom {nFactors} | R Documentation |
Identify the Data Type to Obtain the Eigenvalues From
Description
The eigenFrom
function identifies the data type to obtain the
eigenvalues from. The function is used internally in many fonctions of
the nFactors to be able to apply these to a vector of eigenvalues,
a matrix of correlations or covariance or a data.frame
.
Usage
eigenFrom(x)
Arguments
x |
numeric: a vector of eigenvalues, a matrix of
correlations or of covariances or a data.frame of data |
Value
value |
character: return the data type to obtain the eigenvalues from:
"eigenvalues" , "correlation" or "data" |
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
# Examples of adequate data sources
# Vector of eigenvalues
data(dFactors)
x1 <- dFactors$Cliff1$eigenvalues
eigenFrom(x1)
# Data from a data.frame
x2 <- data.frame(matrix(20*rnorm(100), ncol=5))
eigenFrom(x2)
# From a covariance matrix
x3 <- cov(x2)
eigenFrom(x3)
# From a correlation matrix
x4 <- cor(x2)
eigenFrom(x4)
# Examples of inadequate data sources: not run because of errors generated
# x0 <- c(2,1) # Error: not enough eigenvalues
# eigenFrom(x0)
# x2 <- matrix(x1, ncol=5) # Error: non a symetric covariance matrix
# eigenFrom(x2)
# eigenFrom(x3[,(1:2)]) # Error: not enough variables
# x6 <- table(x5) # Error: not a valid data class
# eigenFrom(x6)
# .......................................................
[Package
nFactors version 2.3.1
Index]