sirt_eigenvalues: First Eigenvalues of a Symmetric Matrix

Description Usage Arguments Value References Examples

View source: R/sirt_eigenvalues.R

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

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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

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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)

sirt documentation built on Feb. 18, 2020, 1:08 a.m.