{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T11:53:36Z","timestamp":1790769216277,"version":"4.1.0"},"reference-count":47,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2016,8,19]],"date-time":"2016-08-19T00:00:00Z","timestamp":1471564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["CRC 803\u2013Z2"],"award-info":[{"award-number":["CRC 803\u2013Z2"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["FOR 916\u2013B3"],"award-info":[{"award-number":["FOR 916\u2013B3"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,9,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n                  <jats:p>We propose, a heterogeneous simultaneous multiscale change point estimator called \u2018H-SMUCE\u2019 for the detection of multiple change points of the signal in a heterogeneous Gaussian regression model. A piecewise constant function is estimated by minimizing the number of change points over the acceptance region of a multiscale test which locally adapts to changes in the variance. The multiscale test is a combination of local likelihood ratio tests which are properly calibrated by scale-dependent critical values to keep a global nominal level \u03b1, even for finite samples. We show that H-SMUCE controls the error of overestimation and underestimation of the number of change points. For this, new deviation bounds for F-type statistics are derived. Moreover, we obtain confidence sets for the whole signal. All results are non-asymptotic and uniform over a large class of heterogeneous change point models. H-SMUCE is fast to compute, achieves the optimal detection rate and estimates the number of change points at almost optimal accuracy for vanishing signals, while still being robust. We compare H-SMUCE with several state of the art methods in simulations and analyse current recordings of a transmembrane protein in the bacterial outer membrane with pronounced heterogeneity for its states. An R-package is available on line.<\/jats:p>","DOI":"10.1111\/rssb.12202","type":"journal-article","created":{"date-parts":[[2016,8,19]],"date-time":"2016-08-19T12:26:43Z","timestamp":1471609603000},"page":"1207-1227","source":"Crossref","is-referenced-by-count":56,"title":["Heterogeneous Change Point Inference"],"prefix":"10.1093","volume":"79","author":[{"given":"Florian","family":"Pein","sequence":"first","affiliation":[{"name":"Georg-August-Universit\u00e4t G\u00f6ttingen \u00a0 Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hannes","family":"Sieling","sequence":"additional","affiliation":[{"name":"Georg-August-Universit\u00e4t G\u00f6ttingen \u00a0 Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Axel","family":"Munk","sequence":"additional","affiliation":[{"name":"Georg-August-Universit\u00e4t G\u00f6ttingen and Max Planck Institute for Biophysical Chemistry , G\u00f6ttingen , Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2016,8,19]]},"reference":[{"key":"2023021709330977900_rssb12202-cit-0001","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1007\/s11222-010-9196-x","article-title":"Segmentation of the mean of heteroscedastic data via crossvalidation","volume":"21","author":"Arlot","year":"2011","journal-title":"Statist. 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