{"title":"多元情况下缺失值的一种新算法","authors":"I. Almasi, Mohsen Salehi, M. Moradi","doi":"10.52547/JIRSS.19.2.133","DOIUrl":null,"url":null,"abstract":". There are several methods to make inferences about the parameters of the sampling distribution when we encounter the missing values and the censored data. In this paper, through the order statistics and the projection theorem, a novel algorithm is proposed to impute the missing values in the multivariate case. Then, the performance of this method is investigated through the simulation studies. In an attempt to validate the proposed method and compare it with some other methods a real data is used.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.1000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Algorithm to Impute the Missing Values in the Multivariate Case\",\"authors\":\"I. Almasi, Mohsen Salehi, M. Moradi\",\"doi\":\"10.52547/JIRSS.19.2.133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". There are several methods to make inferences about the parameters of the sampling distribution when we encounter the missing values and the censored data. In this paper, through the order statistics and the projection theorem, a novel algorithm is proposed to impute the missing values in the multivariate case. Then, the performance of this method is investigated through the simulation studies. In an attempt to validate the proposed method and compare it with some other methods a real data is used.\",\"PeriodicalId\":42965,\"journal\":{\"name\":\"JIRSS-Journal of the Iranian Statistical Society\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.1000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JIRSS-Journal of the Iranian Statistical Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52547/JIRSS.19.2.133\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JIRSS-Journal of the Iranian Statistical Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52547/JIRSS.19.2.133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
A New Algorithm to Impute the Missing Values in the Multivariate Case
. There are several methods to make inferences about the parameters of the sampling distribution when we encounter the missing values and the censored data. In this paper, through the order statistics and the projection theorem, a novel algorithm is proposed to impute the missing values in the multivariate case. Then, the performance of this method is investigated through the simulation studies. In an attempt to validate the proposed method and compare it with some other methods a real data is used.
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