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2019 Multiple changepoint detection with partial information on changepoint times
Yingbo Li, Robert Lund, Anuradha Hewaarachchi
Electron. J. Statist. 13(2): 2462-2520 (2019). DOI: 10.1214/19-EJS1568

Abstract

This paper proposes a new minimum description length procedure to detect multiple changepoints in time series data when some times are a priori thought more likely to be changepoints. This scenario arises with temperature time series homogenization pursuits, our focus here. Our Bayesian procedure constructs a natural prior distribution for the situation, and is shown to estimate the changepoint locations consistently, with an optimal convergence rate. Our methods substantially improve changepoint detection power when prior information is available. The methods are also tailored to bivariate data, allowing changes to occur in one or both component series.

Citation

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Yingbo Li. Robert Lund. Anuradha Hewaarachchi. "Multiple changepoint detection with partial information on changepoint times." Electron. J. Statist. 13 (2) 2462 - 2520, 2019. https://doi.org/10.1214/19-EJS1568

Information

Received: 1 November 2017; Published: 2019
First available in Project Euclid: 25 July 2019

zbMATH: 1422.62286
MathSciNet: MR3984259
Digital Object Identifier: 10.1214/19-EJS1568

Subjects:
Primary: 62C12, 62F10, 62M10

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Vol.13 • No. 2 • 2019
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