BayesProject (version 1.0)

summaxcusum: Cpp implementation of sum-cusum and max-cusum for single changepoint detection.

Description

Detects one multivariate changepoint in a dataset using the sum-cusum or max-cusum technique. Solely required is the dataset as first parameter. The testing threshold ("threshold") is chosen automatically if missing. The parameter "sum_cusum" (default TRUE) indicates if sum-cusum or max-cusum is used.

Usage

summaxcusum(x, threshold, sum_cusum = TRUE, rescale.var = TRUE)

Arguments

x

A \(p \times n\) matrix representing \(p\) data series having \(n\) observations each.

threshold

The testing threshold to detect the single changepoint. If missing, parameter will be calibrated automatically.

sum_cusum

A boolean flag to indicate if sum cusum (sum_cusum=T) or max cusum (sum_cusum=F) is used. Default is TRUE.

rescale.var

A boolean flag to indicate if the variance should be rescaled before detecting a changepoint. Default is TRUE.

References

Hahn, G., Fearnhead, P., Eckley, I.A. (2020). Fast computation of a projection direction for multivariate changepoint detection. Stat Comput.

Examples

# NOT RUN {
library(BayesProject)
data(testdata)
resSumCusum <- summaxcusum(testdata,sum_cusum=TRUE)
print(resSumCusum$cpt)
resMaxCusum <- summaxcusum(testdata,sum_cusum=FALSE)
print(resMaxCusum$cpt)

# }