post.processing: Post-processing of the change-points
In wbsts: Multiple Change-Point Detection for Nonstationary Time Series

A function to control the number of change-points estimated from the WBS algorithm and to reduce the risk of over-segmentation.

1	post.processing(z,br,del=-1,epp=-1,C_i=NULL,scales=NULL)

`z`	The wavelet periodogram matrix.
`br`	The change-points to be post-processed.
`del`	The minimum allowed size of a segment.
`epp`	A minimum adjustment for the bias present in E^{(i)}_{t,T}.
`C_i`	The CUSUM threshold.
`scales`	Which wavelet periodogram scales to be used.

K. Korkas and P. Fryzlewicz (2017), Multiple change-point detection for non-stationary time series using Wild Binary Segmentation. Statistica Sinica, 27, 287-311. (http://stats.lse.ac.uk/fryzlewicz/WBS_LSW/WBS_LSW.pdf)

wbsts documentation built on July 1, 2020, 5:23 p.m.