{"title":"混合条件下的非参数回归可加性检验","authors":"Christine Camlong-Viot","doi":"10.1016/S0764-4442(01)02146-2","DOIUrl":null,"url":null,"abstract":"<div><p>In the setting of additive models, this paper studies kernel marginal integration estimates. These estimates are used for the construction of a test of additivity. We propose to show the asymptotic normality of a test statistic under conditions of absolute regularity.</p></div>","PeriodicalId":100300,"journal":{"name":"Comptes Rendus de l'Académie des Sciences - Series I - Mathematics","volume":"333 9","pages":"Pages 877-880"},"PeriodicalIF":0.0000,"publicationDate":"2001-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0764-4442(01)02146-2","citationCount":"6","resultStr":"{\"title\":\"Vers un test d'additivité en régression non paramétrique sous des conditions de mélange\",\"authors\":\"Christine Camlong-Viot\",\"doi\":\"10.1016/S0764-4442(01)02146-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In the setting of additive models, this paper studies kernel marginal integration estimates. These estimates are used for the construction of a test of additivity. We propose to show the asymptotic normality of a test statistic under conditions of absolute regularity.</p></div>\",\"PeriodicalId\":100300,\"journal\":{\"name\":\"Comptes Rendus de l'Académie des Sciences - Series I - Mathematics\",\"volume\":\"333 9\",\"pages\":\"Pages 877-880\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S0764-4442(01)02146-2\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Comptes Rendus de l'Académie des Sciences - Series I - Mathematics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0764444201021462\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comptes Rendus de l'Académie des Sciences - Series I - Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0764444201021462","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vers un test d'additivité en régression non paramétrique sous des conditions de mélange
In the setting of additive models, this paper studies kernel marginal integration estimates. These estimates are used for the construction of a test of additivity. We propose to show the asymptotic normality of a test statistic under conditions of absolute regularity.
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