{"title":"具有变量误差的递归非参数回归","authors":"Xing-Min Chen, Chao Gao","doi":"10.1109/CHICC.2015.7259956","DOIUrl":null,"url":null,"abstract":"Recursive estimation for nonparametric regression with errors in variables is considered in this paper. Based on the deconvolution kernel, recursive estimate for the regression function is given. Strong consistency is established when observation noises are ordinary smooth or supper smooth. Finally a numerical simulation is provided to justify the theoretical analysis.","PeriodicalId":421276,"journal":{"name":"2015 34th Chinese Control Conference (CCC)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recursive nonparametric regression with errors in variables\",\"authors\":\"Xing-Min Chen, Chao Gao\",\"doi\":\"10.1109/CHICC.2015.7259956\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recursive estimation for nonparametric regression with errors in variables is considered in this paper. Based on the deconvolution kernel, recursive estimate for the regression function is given. Strong consistency is established when observation noises are ordinary smooth or supper smooth. Finally a numerical simulation is provided to justify the theoretical analysis.\",\"PeriodicalId\":421276,\"journal\":{\"name\":\"2015 34th Chinese Control Conference (CCC)\",\"volume\":\"193 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 34th Chinese Control Conference (CCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CHICC.2015.7259956\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 34th Chinese Control Conference (CCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CHICC.2015.7259956","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recursive nonparametric regression with errors in variables
Recursive estimation for nonparametric regression with errors in variables is considered in this paper. Based on the deconvolution kernel, recursive estimate for the regression function is given. Strong consistency is established when observation noises are ordinary smooth or supper smooth. Finally a numerical simulation is provided to justify the theoretical analysis.