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

In BayesProject: Fast Projection Direction for Multivariate 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

library(BayesProject)
data(testdata)
resSumCusum <- summaxcusum(testdata,sum_cusum=TRUE)
print(resSumCusum$cpt)
resMaxCusum <- summaxcusum(testdata,sum_cusum=FALSE)
print(resMaxCusum$cpt)

BayesProject documentation built on Oct. 23, 2020, 5:18 p.m.