# Principal Components Analysis from the mixOmics package

### Description

Performs a principal components analysis from the `pca`

function of the `mixOmics`

package.

### Usage

1 2 3 |

### Arguments

`X` |
a numeric matrix (or data frame) which provides the data for the principal components analysis. It can contain missing values. |

`ncomp` |
integer, if data is complete |

`center` |
a logical value indicating whether the variables should be shifted to be zero centered.
Alternately, a vector of length equal the number of columns of |

`scale` |
a logical value indicating whether the variables should be scaled to have
unit variance before the analysis takes place. The default is |

`max.iter` |
integer, the maximum number of iterations in the NIPALS algorithm. |

`tol` |
a positive real, the tolerance used in the NIPALS algorithm. |

`...` |
not used. |

### Details

see `pca`

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