Maria Rosaria Formica, Eugeny Ostrovsky, Leonid Sirota
{"title":"Confidence regions for the multidimensional density in the uniform norm based on the recursive Wolverton-Wagner estimation","authors":"Maria Rosaria Formica, Eugeny Ostrovsky, Leonid Sirota","doi":"arxiv-2409.01451","DOIUrl":null,"url":null,"abstract":"We construct an optimal exponential tail decreasing confidence region for an\nunknown density of distribution in the Lebesgue-Riesz as well as in the\nuniform} norm, built on the sample of the random vectors based of the famous\nrecursive Wolverton-Wagner density estimation.","PeriodicalId":501379,"journal":{"name":"arXiv - STAT - Statistics Theory","volume":"75 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Statistics Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.01451","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We construct an optimal exponential tail decreasing confidence region for an
unknown density of distribution in the Lebesgue-Riesz as well as in the
uniform} norm, built on the sample of the random vectors based of the famous
recursive Wolverton-Wagner density estimation.