get.svd: Singular Value Decomposition

Description Usage Arguments Value Note Author(s) See Also Examples

View source: R/get.svd.r

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

1
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

1
2
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.