Hotelling's test for testing one Euclidean population mean vector.

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`x` |
A matrix containing Euclidean data. |

`a` |
The significance level, set to 0.05 by default. |

`M` |
The hypothesized mean vector. |

`R` |
If R is 1 no bootstrap calibration is performed and the classical p-value via the F distribution is returned. If R is greater than 1, the bootstrap p-value is returned. |

`graph` |
A boolean variable which is taken into consideration only when bootstrap calibration is performed. IF TRUE the histogram of the bootstrap test statistic values is plotted. |

Multivariate hypothesis test for a one sample mean vector. This is the multivariate analogue of the one sample t-test. The p-value can be calculated either asymptotically or via bootstrap.

A list including:

`m` |
The sample mean vector. |

`info` |
The test statistic, the p-value, the critical value and the degrees of freedom of the F distribution (numerator and denominator). This is given if no bootstrap calibration is employed. |

`pvalue` |
The bootstrap p-value is bootstrap is employed. |

`runtime` |
The runtime of the bootstrap calibration. |

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Giorgos Athineou <athineou@csd.uoc.gr>

K.V. Mardia, J.T. Kent and J.M. Bibby (1979). Multivariate analysis.

```
eel.test1, el.test1, james, hotel2T2, maov, el.test2, comp.test
```

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