Description Usage Arguments Value Author(s)

Detect and filter distance matrix for potential outliers by heuristical detection. The distance matrix is pruned using the following criterion until no further outliers are found:

Compute distance threshold by computing

`quant`

quantile of the entire distance matrixFind and remove the most extreme data point defined by highest median distance to other data if it has less than

`n_neighbour`

neighbours closer than threshold to itselfReturn to the first step and continue until no further data points are pruned.

1 | ```
filter_dist_outliers(d, quant = 0.8, n_neighbour = 1)
``` |

`d` |
distance matrix as matrix |

`quant` |
quantile of all distances to use as a filtering threshold |

`n_neighbour` |
number of neighbours required |

filtered distance matrix, or NULL if all samples were pruned

Tommi Vatanen <[email protected]>

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