sirt_eigenvalues: First Eigenvalues of a Symmetric Matrix

In alexanderrobitzsch/sirt: Supplementary Item Response Theory Models

First Eigenvalues of a Symmetric Matrix

Description

This function computes the first D eigenvalues and eigenvectors of a symmetric positive definite matrices. The eigenvalues are computed by the Rayleigh quotient method (Lange, 2010, p. 120).

Usage

sirt_eigenvalues( X, D, maxit=200, conv=10^(-6) )

Arguments

X	Symmetric matrix
D	Number of eigenvalues to be estimated
maxit	Maximum number of iterations
conv	Convergence criterion

Value

A list with following entries:

d	Vector of eigenvalues
u	Matrix with eigenvectors in columns

References

Lange, K. (2010). Numerical Analysis for Statisticians. New York: Springer.

Examples

Sigma <- diag(1,3)
Sigma[ lower.tri(Sigma) ] <- Sigma[ upper.tri(Sigma) ] <- c(.4,.6,.8 )
sirt::sirt_eigenvalues(X=Sigma, D=2 )
# compare with svd function
svd(Sigma)

alexanderrobitzsch/sirt documentation built on Dec. 1, 2024, 2:18 a.m.