Outlier Detection

Description

This function calculates outlier's using geodesic distances of the SRVFs from the median

Usage

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outlier.detection(q, time, mq, k = 1.5)

Arguments

q

matrix (N x M) of M SRVF functions with N samples

time

vector of size N describing the sample points

mq

median calcuated using time_warping

k

cutoff threshold (default = 1.5)

Value

q_outlier

outlier functions

References

Srivastava, A., Wu, W., Kurtek, S., Klassen, E., Marron, J. S., May 2011. Registration of functional data using fisher-rao metric, arXiv:1103.3817v2 [math.ST].

Tucker, J. D., Wu, W., Srivastava, A., Generative Models for Function Data using Phase and Amplitude Separation, Computational Statistics and Data Analysis (2012), 10.1016/j.csda.2012.12.001.

Examples

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data("toy_data")
data("toy_warp")
q_outlier = outlier.detection(toy_warp$q0,toy_data$time,toy_warp$mqn,k=.1)

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