{"title":"一类独立但不相同分布的观测值的最大似然理论","authors":"Fang-kuo Sun, T. Lee","doi":"10.1109/CDC.1978.268023","DOIUrl":null,"url":null,"abstract":"In this paper, maximum likelihood estimates of the mean and the covariance of a normal random variable, based on a set of independently, but nonidentically distributed observations, are discussed. An efficient algorithm for computing MLEs is introduced. The asymptotic properties such as strong consistency and asymptotic normality are examined.","PeriodicalId":375119,"journal":{"name":"1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Maximum likelihood theory for a class of independently, but nonidentically distributed observations\",\"authors\":\"Fang-kuo Sun, T. Lee\",\"doi\":\"10.1109/CDC.1978.268023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, maximum likelihood estimates of the mean and the covariance of a normal random variable, based on a set of independently, but nonidentically distributed observations, are discussed. An efficient algorithm for computing MLEs is introduced. The asymptotic properties such as strong consistency and asymptotic normality are examined.\",\"PeriodicalId\":375119,\"journal\":{\"name\":\"1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1978.268023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1978.268023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Maximum likelihood theory for a class of independently, but nonidentically distributed observations
In this paper, maximum likelihood estimates of the mean and the covariance of a normal random variable, based on a set of independently, but nonidentically distributed observations, are discussed. An efficient algorithm for computing MLEs is introduced. The asymptotic properties such as strong consistency and asymptotic normality are examined.