confint.multiscale.cpts: Confidence intervals for change points

In mosum: Moving Sum Based Procedures for Changes in the Mean

Confidence intervals for change points

Description

Generate bootstrap confidence intervals for change points.

Usage

## S3 method for class 'multiscale.cpts'
confint(object, parm = "cpts", level = 0.05, N_reps = 1000, ...)

Arguments

object	an object of class multiscale.cpts
parm	specification of which parameters are to be given confidence intervals; parm = "cpts" is supported
level	numeric value in (0, 1), such that the 100(1-level)% confidence bootstrap intervals are computed
N_reps	number of bootstrap replications
...	not in use

Details

See the referenced literature for further details

Value

S3 object of class cpts.ci, containing the following fields:

level, N_reps	input parameters
CI	data frame of five columns, containing the estimated change points (column cpts), the pointwise confidence intervals (columns pw.left and pw.right) and the uniform confidence intervals (columns unif.left and unif.right) for the corresponding change points

References

A. Meier, C. Kirch and H. Cho (2021) mosum: A Package for Moving Sums in Change-point Analysis. Journal of Statistical Software, Volume 97, Number 8, pp. 1-42. <doi:10.18637/jss.v097.i08>.

H. Cho and C. Kirch (2022) Bootstrap confidence intervals for multiple change points based on moving sum procedures. Computational Statistics & Data Analysis, Volume 175, pp. 107552.

Examples

x <- testData(lengths = rep(100, 3), means = c(0, 3, 1), sds = rep(1, 3), seed = 1337)$x
mlp <-  multiscale.localPrune(x, G = c(8, 15, 30, 70))
ci <- confint(mlp, N_reps = 5000)
print(ci$CI)

mosum documentation built on Oct. 22, 2022, 5:05 p.m.