{"title":"一类广义变核回归估计量","authors":"Sharada V. Bhat, Bhargavi Deshpande","doi":"10.12785/IJCTS/060205","DOIUrl":null,"url":null,"abstract":"Nadaraya-Watson (NW) estimator with fixed bandwidth and its adaptive forms with varying bandwidths are widely used kernel regression estimators in nonparametric regression. In this paper, we propose a generalized class of varying kernel regression estimators with its members based on various statistical measures of pilot density estimates. We study the performance of the members of this class in terms of mean integrated squared error (MISE).","PeriodicalId":130559,"journal":{"name":"International Journal of Computational & Theoretical Statistics","volume":"132 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Generalized Class of Varying Kernel Regression Estimators\",\"authors\":\"Sharada V. Bhat, Bhargavi Deshpande\",\"doi\":\"10.12785/IJCTS/060205\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nadaraya-Watson (NW) estimator with fixed bandwidth and its adaptive forms with varying bandwidths are widely used kernel regression estimators in nonparametric regression. In this paper, we propose a generalized class of varying kernel regression estimators with its members based on various statistical measures of pilot density estimates. We study the performance of the members of this class in terms of mean integrated squared error (MISE).\",\"PeriodicalId\":130559,\"journal\":{\"name\":\"International Journal of Computational & Theoretical Statistics\",\"volume\":\"132 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computational & Theoretical Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12785/IJCTS/060205\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational & Theoretical Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12785/IJCTS/060205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Generalized Class of Varying Kernel Regression Estimators
Nadaraya-Watson (NW) estimator with fixed bandwidth and its adaptive forms with varying bandwidths are widely used kernel regression estimators in nonparametric regression. In this paper, we propose a generalized class of varying kernel regression estimators with its members based on various statistical measures of pilot density estimates. We study the performance of the members of this class in terms of mean integrated squared error (MISE).
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