Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Relating and Comparing Methods for Detecting Changes in Mean
AU - Fearnhead, Paul
AU - Rigaill, Guillem
PY - 2020/12/1
Y1 - 2020/12/1
N2 - In recent years there have been a large number of proposed approaches to detecting changes in mean. A natural question for an analyst is which method is most appropriate for their application. Answering this question is difficult because current empirical studies often give conflicting conclusions. This paper aims to show the similarities and differences between different changepoint methods. We highlight that there are two aspects to estimating changepoints: estimating the number of changes and estimating their location, and that comparisons should separately evaluate these two aspects. We perform an extensive comparison of different methods across a range of simulation scenarios, and provide code and full results for an interested practitioner to extend this comparison to more methods or different scenarios.
AB - In recent years there have been a large number of proposed approaches to detecting changes in mean. A natural question for an analyst is which method is most appropriate for their application. Answering this question is difficult because current empirical studies often give conflicting conclusions. This paper aims to show the similarities and differences between different changepoint methods. We highlight that there are two aspects to estimating changepoints: estimating the number of changes and estimating their location, and that comparisons should separately evaluate these two aspects. We perform an extensive comparison of different methods across a range of simulation scenarios, and provide code and full results for an interested practitioner to extend this comparison to more methods or different scenarios.
U2 - 10.1002/sta4.291
DO - 10.1002/sta4.291
M3 - Journal article
VL - 9
JO - Stat
JF - Stat
SN - 2049-1573
IS - 1
M1 - e291
ER -