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 matrix
Find 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 itself
Return to the first step and continue until no further data points are pruned.
filter_dist_outliers(d, quant = 0.8, n_neighbour = 1)
distance matrix as matrix
quantile of all distances to use as a filtering threshold
number of neighbours required
filtered distance matrix, or NULL if all samples were pruned
Tommi Vatanen <[email protected]>
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