{"title":"稀疏伽玛尺度混合模型的检测边界","authors":"Michael I. Stewart","doi":"10.1111/anzs.12347","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>We derive the detection boundary for the one-sided version of the gamma scale mixture model where the contaminating component has a larger mean than the known reference distribution. We also derive an adaptive test which is able to almost uniformly attain the best possible performance in terms of detection of local alternatives.</p>\n </div>","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Detection boundary for a sparse gamma scale mixture model\",\"authors\":\"Michael I. Stewart\",\"doi\":\"10.1111/anzs.12347\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>We derive the detection boundary for the one-sided version of the gamma scale mixture model where the contaminating component has a larger mean than the known reference distribution. We also derive an adaptive test which is able to almost uniformly attain the best possible performance in terms of detection of local alternatives.</p>\\n </div>\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2022-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/anzs.12347\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/anzs.12347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection boundary for a sparse gamma scale mixture model
We derive the detection boundary for the one-sided version of the gamma scale mixture model where the contaminating component has a larger mean than the known reference distribution. We also derive an adaptive test which is able to almost uniformly attain the best possible performance in terms of detection of local alternatives.