Description Usage Arguments Value Author(s) See Also

Calculates the covariance matrix of the normally standardized variables obtained from the columns of `x`

1 2 3 4 |

`x` |
variable |

`data` |
a sample of data on which a non-parametric pghjjrobability distribution is estimated |

`cpf` |
cumulative probability distribution. If |

`mean` |
mean (expected value) of the normalized random variable. Default is 0. |

`sd` |
standard deviation of the normalized random variable. Default is 1. |

`step` |
vector of values in which step discontinuities of the cumulative probability function occur. Default is |

`prec` |
amplitude of the neighbourhood of the step discontinuities where cumulative probability function is treated as non continuous. |

`use` |
see |

`type` |
see |

`extremes` |
logical variable.
If
where |

`sample` |
information about sample or probability distribution. Default is |

`origin_x` |
date corresponding to the first row of |

`origin_data` |
date corresponding to the first row of |

a matrix with the normalized variable or its inverse

Emanuele Cordano, Emanuele Eccel

`normalizeGaussian_severalstations`

,`normalizeGaussian`

@note It applies `normalizeGaussian_severalstations`

to `x`

and `data`

and then calculates the covariances among the column.
See the R code for further details

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