svd.triplet {FactoMineR} | R Documentation |

## Singular Value Decomposition of a Matrix

### Description

Compute the singular-value decomposition of a rectangular matrix with weights for rows and columns.

### Usage

```
svd.triplet(X, row.w=NULL, col.w=NULL, ncp=Inf)
```

### Arguments

`X` |
a data matrix |

`row.w` |
vector with the weights of each row (NULL by default and the weights are uniform) |

`col.w` |
vector with the weights of each column (NULL by default and the weights are uniform) |

`ncp` |
the number of components kept for the outputs |

### Value

`vs` |
a vector containing the singular values of 'x'; |

`u` |
a matrix whose columns contain the left singular vectors of 'x'; |

`v` |
a matrix whose columns contain the right singular vectors of 'x'. |

### See Also

[Package

*FactoMineR*version 2.11 Index]