具有可分离协方差矩阵结构的多元线性模型的最大似然算法的性质

Biometrical Letters Pub Date : 2021-06-01 DOI:10.2478/bile-2021-0005

A. Szczepańska-Álvarez, B. Zawieja, Adolfo Álvarez

{"title":"具有可分离协方差矩阵结构的多元线性模型的最大似然算法的性质","authors":"A. Szczepańska-Álvarez, B. Zawieja, Adolfo Álvarez","doi":"10.2478/bile-2021-0005","DOIUrl":null,"url":null,"abstract":"Summary In this paper we present properties of an algorithm to determine the maximum likelihood estimators of the covariance matrix when two processes jointly affect the observations. Additionally, one process is partially modeled by a compound symmetry structure. We perform a simulation study of the properties of an iteratively determined estimator of the covariance matrix.","PeriodicalId":8933,"journal":{"name":"Biometrical Letters","volume":"2016 1","pages":"69 - 79"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Properties of an MLE algorithm for the multivariate linear model with a separable covariance matrix structure\",\"authors\":\"A. Szczepańska-Álvarez, B. Zawieja, Adolfo Álvarez\",\"doi\":\"10.2478/bile-2021-0005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary In this paper we present properties of an algorithm to determine the maximum likelihood estimators of the covariance matrix when two processes jointly affect the observations. Additionally, one process is partially modeled by a compound symmetry structure. We perform a simulation study of the properties of an iteratively determined estimator of the covariance matrix.\",\"PeriodicalId\":8933,\"journal\":{\"name\":\"Biometrical Letters\",\"volume\":\"2016 1\",\"pages\":\"69 - 79\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biometrical Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/bile-2021-0005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biometrical Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/bile-2021-0005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

本文给出了当两个过程共同影响观测值时确定协方差矩阵最大似然估计的算法的性质。另外，其中一个过程部分由复合对称结构建模。我们对协方差矩阵的迭代确定估计量的性质进行了模拟研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Properties of an MLE algorithm for the multivariate linear model with a separable covariance matrix structure

Summary In this paper we present properties of an algorithm to determine the maximum likelihood estimators of the covariance matrix when two processes jointly affect the observations. Additionally, one process is partially modeled by a compound symmetry structure. We perform a simulation study of the properties of an iteratively determined estimator of the covariance matrix.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Biometrical Letters

自引率

0.00%

发文量