svd.inverse: SVD Inverse of a square matrix

In matrixcalc: Collection of Functions for Matrix Calculations

SVD Inverse of a square matrix

Description

This function returns the inverse of a matrix using singular value decomposition. If the matrix is a square matrix, this should be equivalent to using the solve function. If the matrix is not a square matrix, then the result is the Moore-Penrose pseudo inverse.

Usage

svd.inverse(x)

Arguments

x	a numeric matrix

Value

A matrix.

Author(s)

Frederick Novomestky [e-mail]

References

Bellman, R. (1987). Matrix Analysis, Second edition, Classics in Applied Mathematics, Society for Industrial and Applied Mathematics.

Examples

A <- matrix( c ( 1, 2, 2, 1 ), nrow=2, byrow=TRUE)
invA <- svd.inverse( A )
print( A )
print( invA )
print( A %*% invA )
B <- matrix( c( -1, 2, 2 ), nrow=1, byrow=TRUE )
invB <- svd.inverse( B )
print( B )
print( invB )
print( B %*% invB )

matrixcalc documentation built on Sept. 15, 2022, 1:05 a.m.