quantiles: Estimated Quantiles for the Open-end Nonparametric Sequential...

In npcp: Some Nonparametric CUSUM Tests for Change-Point Detection in Possibly Multivariate Observations

Estimated Quantiles for the Open-end Nonparametric Sequential Change-Point Detection Tests

Description

Estimated quantiles for the open-end nonparametric sequential change-point detection tests described in seqOpenEndCpMean and seqOpenEndCpDist. More details can be found in the references below.

Usage

data("quantiles")

Format

list of 6 elements. The first 5 are arrays containing the estimated 90%, 95% and 99% quantiles necessary for carrying out the sequential tests described in seqOpenEndCpMean. The last element is a list containing the estimated 90%, 95% and 99% quantiles as well as other estimated parameters necessary for carrying out the sequential test described in seqOpenEndCpDist.

References

J. Gösmann, T. Kley and H. Dette (2021), A new approach for open-end sequential change point monitoring, Journal of Time Series Analysis 42:1, pages 63-84, https://arxiv.org/abs/1906.03225.

M. Holmes and I. Kojadinovic (2021), Open-end nonparametric sequential change-point detection based on the retrospective CUSUM statistic, Electronic Journal of Statistics 15:1, pages 2288-2335, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1214/21-EJS1840")}.

L. Horváth, M. Hušková, P. Kokoszka and J. Steinebach (2004). Monitoring changes in linear models. Journal of Statistical Planning and Inference 126, pages 225-251.

M. Holmes, I. Kojadinovic and A. Verhoijsen (2022), Multi-purpose open-end monitoring procedures for multivariate observations based on the empirical distribution function, 45 pages, https://arxiv.org/abs/2201.10311.

Examples

data("quantiles")
str(quantiles)

npcp documentation built on Oct. 18, 2024, 9:06 a.m.