Description Usage Arguments Value Note Author(s) Examples

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

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

`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 |

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

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

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

1 2 3 4 5 6 | ```
#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
``` |

```
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
```

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