{"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/spatio-temporal-bayesian-on-line-changepoint","title":"Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection","arxiv_id":"1805.05383","date":"2018-05-14","proceeding":"ICML 2018 7","authors":["Jeremias Knoblauch","Theodoros Damoulas"],"abstract":"Bayesian On-line Changepoint Detection is extended to on-line model selection\nand non-stationary spatio-temporal processes. We propose spatially structured\nVector Autoregressions (VARs) for modelling the process between changepoints\n(CPs) and give an upper bound on the approximation error of such models. The\nresulting algorithm performs prediction, model selection and CP detection\non-line. Its time complexity is linear and its space complexity constant, and\nthus it is two orders of magnitudes faster than its closest competitor. In\naddition, it outperforms the state of the art for multivariate data.","url_abs":"http://arxiv.org/abs/1805.05383v2","url_pdf":"http://arxiv.org/pdf/1805.05383v2.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":"spatio-temporal-bayesian-on-line-changepoint","repo_url":"https://github.com/alan-turing-institute/bocpdms","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"change-point-detection","task_name":"Change Point Detection"},{"task_slug":"model-selection","task_name":"Model Selection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}