{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T20:03:19Z","timestamp":1790971399368,"version":"4.1.0"},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T00:00:00Z","timestamp":1677196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>We consider the problem of designing experiments to detect the presence of a specified heteroscedastity in Gaussian regression models. We study the relationship of the Ds- and KL-criteria with the noncentrality parameter of the asymptotic chi-squared distribution of a likelihood-based test, for local alternatives. We found that, when the heteroscedastity depends on one parameter, the two criteria coincide asymptotically and that the D1-criterion is proportional to the noncentrality parameter. Differently, when it depends on several parameters, the KL-optimum design converges to the design that maximizes the noncentrality parameter. Our theoretical findings are confirmed through a simulation study.<\/jats:p>","DOI":"10.1093\/jrsssb\/qkad004","type":"journal-article","created":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T18:09:38Z","timestamp":1677262178000},"page":"315-326","source":"Crossref","is-referenced-by-count":7,"title":["Designing to detect heteroscedasticity in a regression model"],"prefix":"10.1093","volume":"85","author":[{"given":"Alessandro","family":"Lanteri","sequence":"first","affiliation":[{"name":"Department of Economics, Management and Quantitative Methods, University of Milan , Milano , Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samantha","family":"Leorato","sequence":"additional","affiliation":[{"name":"Department of Economics, Management and Quantitative Methods, University of Milan , Milano , Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jes\u00fas","family":"L\u00f3pez-Fidalgo","sequence":"additional","affiliation":[{"name":"Institute of Data Science and Artificial Intelligence, University of Navarre , Pamplona , Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chiara","family":"Tommasi","sequence":"additional","affiliation":[{"name":"Department of Economics, Management and Quantitative Methods, University of Milan , Milano , Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,2,24]]},"reference":[{"key":"2023050420355345700_qkad004-B1","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780199296590.001.0001","volume-title":"Optimum experimental designs, with SAS","author":"Atkinson","year":"2007"},{"issue":"1","key":"2023050420355345700_qkad004-B2","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1093\/biomet\/62.1.57","article-title":"The design of 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