R: SVD Inverse of a square matrix

svd.inverse {matrixcalc} | R Documentation

## 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 fnovomes@poly.edu

### 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 )

[Package matrixcalc version 1.0-3 Index]