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 numeric vector of observations. s A numeric scalar representing the starting index of an interval. e A numeric scalar representing the ending index of an interval. Alpha An integer vector of starting indices of random intervals. Beta An integer vector of ending indices of random intervals. K A numeric scalar representing the robustification parameter in the Huber loss. delta A positive integer scalar of minimum spacing. 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

thresholdBS for obtaining change points estimation.