gsisvdsolve: Internal function: Solves singular and non square equation...

Description Usage Arguments Value Note Author(s) Examples

Description

Based on the singular value decomposition, a singular equation system ax=b is solved.

Usage

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gsi.svdsolve(a,b,...,cond=1E-10)

Arguments

a

the matrix of ax=b (a.k.a. left-hand side matrix)

b

the vector or matrix b of ax=b (a.k.a right-hand side, independent element)

cond

the smallest-acceptable condition of the matrix. Smaller singular values are truncate

...

additional arguments to svd

Value

The "smallest" vector or matrix solving this system with minimal joint error among all vectors.

Note

Do not use gsi.* functions directly since they are internal functions of the package

Author(s)

K.Gerald v.d. Boogaart http://www.stat.boogaart.de

Examples

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#A <- matrix(c(0,1,0,0,0,0),ncol=2)
#b <- diag(3)
#erg <- gsi.svdsolve(A,b)
#erg
#A %*% erg 
#diag(c(0,1,0))  # richtig

Example output

Loading required package: tensorA

Attaching package: 'tensorA'

The following object is masked from 'package:base':

    norm

Loading required package: robustbase
Loading required package: energy
Loading required package: bayesm
Welcome to compositions, a package for compositional data analysis.
Find an intro with "? compositions"


Attaching package: 'compositions'

The following objects are masked from 'package:stats':

    cor, cov, dist, var

The following objects are masked from 'package:base':

    %*%, scale, scale.default

compositions documentation built on Jan. 5, 2022, 5:09 p.m.