Graphical Influence Diagnostics for Changepoint Models

Wilms, Ines and Killick, Rebecca and Matteson, David S. (2022) Graphical Influence Diagnostics for Changepoint Models. Journal of Computational and Graphical Statistics, 31 (3). pp. 753-765. ISSN 1061-8600

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Abstract

Changepoint models enjoy a wide appeal in a variety of disciplines to model the heterogeneity of ordered data. Graphical influence diagnostics to characterize the influence of single observations on changepoint models are, however, lacking. We address this gap by developing a framework for investigating instabilities in changepoint segmentations and assessing the influence of single observations on various outputs of a changepoint analysis. We construct graphical diagnostic plots that allow practitioners to assess whether instabilities occur; how and where they occur; and to detect influential individual observations triggering instability. We analyze well-log data to illustrate how such influence diagnostic plots can be used in practice to reveal features of the data that may otherwise remain hidden. Supplementary materials for this article are available online.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Computational and Graphical Statistics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1800/1804
Subjects:
ID Code:
161559
Deposited By:
Deposited On:
27 Oct 2021 14:20
Refereed?:
Yes
Published?:
Published
Last Modified:
28 Nov 2022 15:00