BS.cov {changepoints} R Documentation

## Binary Segmentation for covariance change points detection through Operator Norm.

### Description

Perform binary segmentation for covariance change points detection through Operator Norm.

### Usage

BS.cov(X, s, e, level = 0)


### Arguments

 X A numeric matrix of observations with with horizontal axis being time, and vertical axis being dimensions. s A integer scalar of starting index. e A integer scalar of ending index. level A parameter for tracking the level at which a change point is detected. Should be fixed as 0.

### Value

An object of class "BS", which is a list with the structure:

• S: A vector of estimated changepoints (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.

Haotian Xu

### References

Wang, Yu and Rinaldo (2021) <doi:10.3150/20-BEJ1249>.

thresholdBS for obtain change points estimation.

### Examples

p = 10
A1 = gen.cov.mat(p, 1, "equal")
A2 = gen.cov.mat(p, 2, "diagonal")
A3 = gen.cov.mat(p, 3, "power")
X = cbind(t(MASS::mvrnorm(100, mu = rep(0, p), A1)),
t(MASS::mvrnorm(150, mu = rep(0, p), A2)),
t(MASS::mvrnorm(200, mu = rep(0, p), A3)))
temp = BS.cov(X, 1, 450)
thresholdBS(temp, 10)


[Package changepoints version 1.1.0 Index]