| outlier.detection {fdasrvf} | R Documentation |
This function calculates outlier's using geodesic distances of the SRVFs from the median
outlier.detection(q, time, mq, k = 1.5)
q |
matrix (N x M) of M SRVF functions with N samples |
time |
vector of size N describing the sample points |
mq |
median calculated using |
k |
cutoff threshold (default = 1.5) |
q_outlier |
outlier functions |
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.
data("toy_data")
data("toy_warp")
q_outlier = outlier.detection(toy_warp$q0,toy_data$time,toy_warp$mqn,k=.1)