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This function calculates the threshold for the functional depths in order to classify outliers by bootstrapping and fitting a beta distribution. This approach is faster than func_depth_threshold() but makes a Beta distribution assumption for the functional depths which may not always be appropriate.

Usage

func_depth_threshold_beta(data, times, perc = 0.01, B = 10)

Arguments

data

A matrix where each row is an observation of a time series.

times

A vector of length equal to the number of columns as data specifying the time points recorded at.

perc

The percentile of the distribution to use. Default 0.01.

B

The number of bootstraps to use. If 0, distribution is fitted to empirical depths. Default 10.

Value

A numeric giving the threshold.