{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/lagged-exact-bayesian-online-changepoint","title":"Lagged Exact Bayesian Online Changepoint Detection with Parameter Estimation","arxiv_id":"1710.03276","date":"2017-10-09","proceeding":null,"authors":["Michael Byrd","Linh Nghiem","Jing Cao"],"abstract":"Identifying changes in the generative process of sequential data, known as\nchangepoint detection, has become an increasingly important topic for a wide\nvariety of fields. A recently developed approach, which we call EXact Online\nBayesian Changepoint Detection (EXO), has shown reasonable results with\nefficient computation for real time updates. The method is based on a\n\\textit{forward} recursive message-passing algorithm. However, the detected\nchangepoints from these methods are unstable. We propose a new algorithm called\nLagged EXact Online Bayesian Changepoint Detection (LEXO) that improves the\naccuracy and stability of the detection by incorporating $\\ell$-time lags to\nthe inference. The new algorithm adds a recursive \\textit{backward} step to the\nforward EXO and has computational complexity linear in the number of added\nlags. Estimation of parameters associated with regimes is also developed.\nSimulation studies with three common changepoint models show that the detected\nchangepoints from LEXO are much more stable and parameter estimates from LEXO\nhave considerably lower MSE than EXO. We illustrate applicability of the\nmethods with two real world data examples comparing the EXO and LEXO.","url_abs":"http://arxiv.org/abs/1710.03276v3","url_pdf":"http://arxiv.org/pdf/1710.03276v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"lagged-exact-bayesian-online-changepoint","repo_url":"https://github.com/lnghiemum/LEXO","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"parameter-estimation","task_name":"parameter estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}