Description Usage Arguments Details Value Author(s) References Examples

For a given dataset, rFUNTA pseudo-depth values can be obtained. rFUNTA is a robustified functional data depth that is based on the intersection angles that the centered functions form with each other.

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`Data` |
a matrix. Enter the discretized values of a functional data set in a n times T matrix, where n is the number of functional observations and T is the number of time points. |

`centered` |
boolean. If the data are already centered, that means, the mean of each row of |

`type.inner` |
One of |

`type.outer` |
One of |

`tick.dist` |
atomic vector. The distance between two neighbored time points can be set here. Default value is |

`nObs` |
atomic vector. If the dataset has more than one dimension, specify |

The larger the value of FUNTA is, the less it can be regarded as a shape outlier, and vice versa. The values are bounded by 0 and 1.

Vector of rFUNTA values. First observation in `Data`

corresponds to first element of `FUNTA`

.

A. Rehage

Kuhnt, S.; Rehage, A. (2016) An angle-based multivariate functional pseudo-depth for shape outlier detection. *Journal of Multivariate Analysis* 146, 325-340.

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