get.svd: Singular Value Decomposition

In BioPhysConnectoR: BioPhysConnectoR

Description

Computation of the singular value decomposition for a matrix. Sorts the eigenvalues in ascending order by maintaining their original order in an index array.

Usage

get.svd(hessian.mat, linpack = TRUE)

Arguments

hessian.mat	input matrix is a Hessian matrix
linpack	logical, specifies whether LINPACK or LAPACK routines are used

Value

Return value is a list with the following components:

$v	matrix with eigenvectors in each column
$indx	index array for the sorted eigenvalues
$ev	vector with the sorted eigenvalues
$u	matrix with eigenvectors in each column

Note

This function uses the svd() function of R.

Author(s)

Franziska Hoffgaard

See Also

mat.sort, build.hess

Examples

a<-matrix(round(runif(9, 1, 5)), 3, 3)
out<-get.svd(a)

Example output

Loading required package: snow
Loading required package: matrixcalc

BioPhysConnectoR documentation built on May 30, 2017, 6:46 a.m.