WBS.uni.rob {changepoints} | R Documentation |
Robust wild binary segmentation for univariate mean change points detection.
Description
Perform a robust version of the wild binary segmentation method using Huber loss.
Usage
WBS.uni.rob(y, s, e, Alpha, Beta, K = 1.345, delta, level = 0)
Arguments
y |
A |
s |
A |
e |
A |
Alpha |
An |
Beta |
An |
K |
A |
delta |
A positive |
level |
Should be fixed as 0. |
Value
An object of class
"BS", which is a list
with the following structure:
S |
A vector of estimated change points (sorted in strictly increasing order). |
Dval |
A vector of values of CUSUM statistic based on KS distance. |
Level |
A vector representing the levels at which each change point is detected. |
Parent |
A matrix with the starting indices on the first row and the ending indices on the second row. |
Author(s)
Mengchu Li & Haotian Xu
References
Fearnhead & Rigaill (2019) <doi:10.1080/01621459.2017.1385466>.
See Also
thresholdBS
for obtaining change points estimation.