BS.uni.nonpar {changepoints} R Documentation

## Standard binary segmentation for univariate nonparametric change points detection.

### Description

Perform standard binary segmentation for univariate nonparametric change points detection.

### Usage

BS.uni.nonpar(Y, s, e, N, delta, level = 0)


### Arguments

 Y A numeric matrix of observations with horizontal axis being time, and vertical axis being multiple observations on each time point. s A integer scalar of starting index. e A integer scalar of ending index. N A integer vector representing number of multiple observations on each time point. 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.

### References

Padilla, Yu, Wang and Rinaldo (2021) <doi:10.1214/21-EJS1809>.

thresholdBS for obtaining change points estimation, tuneBSuninonpar for a tuning version.
Y = t(as.matrix(c(rnorm(100, 0, 1), rnorm(100, 0, 10), rnorm(100, 0, 40))))
points(x = tail(temp$S[order(temp$Dval)],4), y = Y[,tail(temp$S[order(temp$Dval)],4)], col = "red")