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Autocovariance Estimation in the Presence of Changepoints

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Autocovariance Estimation in the Presence of Changepoints. / Gallagher, Colin; Killick, Rebecca; Lund, Robert et al.
In: Journal of the Korean Statistical Society, Vol. 51, No. 4, 31.12.2022, p. 1021-1040.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Gallagher, C, Killick, R, Lund, R & Shi, X 2022, 'Autocovariance Estimation in the Presence of Changepoints', Journal of the Korean Statistical Society, vol. 51, no. 4, pp. 1021-1040. https://doi.org/10.1007/s42952-022-00173-5

APA

Gallagher, C., Killick, R., Lund, R., & Shi, X. (2022). Autocovariance Estimation in the Presence of Changepoints. Journal of the Korean Statistical Society, 51(4), 1021-1040. https://doi.org/10.1007/s42952-022-00173-5

Vancouver

Gallagher C, Killick R, Lund R, Shi X. Autocovariance Estimation in the Presence of Changepoints. Journal of the Korean Statistical Society. 2022 Dec 31;51(4):1021-1040. Epub 2022 Jun 6. doi: 10.1007/s42952-022-00173-5

Author

Gallagher, Colin ; Killick, Rebecca ; Lund, Robert et al. / Autocovariance Estimation in the Presence of Changepoints. In: Journal of the Korean Statistical Society. 2022 ; Vol. 51, No. 4. pp. 1021-1040.

Bibtex

@article{c9bfd67c03114c3c8b9d0f95ae1ccdad,
title = "Autocovariance Estimation in the Presence of Changepoints",
abstract = "This article studies estimation of a stationary autocovariance structure in the presence of an unknown number of mean shifts. Here, a Yule–Walker moment estimator for the autoregressive parameters in a dependent time series contaminated by mean shift changepoints is proposed and studied. The estimator is based on first order differences of the series and is proven consistent and asymptotically normal when the number of changepoints m and the series length N satisfy m/ N→ 0 as N→ ∞.",
keywords = "Autoregression, Differencing, Robustness, Rolling Windows, Segmentation, Yule-Walker Estimates",
author = "Colin Gallagher and Rebecca Killick and Robert Lund and Xueheng Shi",
note = "The final publication is available at Springer via http://dx.doi.org/10.1007/s42952-022-00173-5",
year = "2022",
month = dec,
day = "31",
doi = "10.1007/s42952-022-00173-5",
language = "English",
volume = "51",
pages = "1021--1040",
journal = "Journal of the Korean Statistical Society",
publisher = "Springer",
number = "4",

}

RIS

TY - JOUR

T1 - Autocovariance Estimation in the Presence of Changepoints

AU - Gallagher, Colin

AU - Killick, Rebecca

AU - Lund, Robert

AU - Shi, Xueheng

N1 - The final publication is available at Springer via http://dx.doi.org/10.1007/s42952-022-00173-5

PY - 2022/12/31

Y1 - 2022/12/31

N2 - This article studies estimation of a stationary autocovariance structure in the presence of an unknown number of mean shifts. Here, a Yule–Walker moment estimator for the autoregressive parameters in a dependent time series contaminated by mean shift changepoints is proposed and studied. The estimator is based on first order differences of the series and is proven consistent and asymptotically normal when the number of changepoints m and the series length N satisfy m/ N→ 0 as N→ ∞.

AB - This article studies estimation of a stationary autocovariance structure in the presence of an unknown number of mean shifts. Here, a Yule–Walker moment estimator for the autoregressive parameters in a dependent time series contaminated by mean shift changepoints is proposed and studied. The estimator is based on first order differences of the series and is proven consistent and asymptotically normal when the number of changepoints m and the series length N satisfy m/ N→ 0 as N→ ∞.

KW - Autoregression

KW - Differencing

KW - Robustness

KW - Rolling Windows

KW - Segmentation

KW - Yule-Walker Estimates

U2 - 10.1007/s42952-022-00173-5

DO - 10.1007/s42952-022-00173-5

M3 - Journal article

VL - 51

SP - 1021

EP - 1040

JO - Journal of the Korean Statistical Society

JF - Journal of the Korean Statistical Society

IS - 4

ER -