{"title":"一类具有二叉家族树的多类型分支过程子代概率的期望最大化估计","authors":"N. Daskalova","doi":"10.1080/08898480.2017.1348723","DOIUrl":null,"url":null,"abstract":"ABSTRACT When proliferating cells are counted in several independent colonies at some time points, the maximum likelihood estimates of the parameters of the multitype branching process are obtained trough an expectation maximization algorithm. In the case of an offspring distribution governed by a Markov branching process with binary family trees, this method, relying then on a partial knowledge of the tree, yields the same estimates as those computed with the complete knowledge of the tree.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"24 1","pages":"246 - 256"},"PeriodicalIF":1.4000,"publicationDate":"2017-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1348723","citationCount":"0","resultStr":"{\"title\":\"Expectation maximization estimates of the offspring probabilities in a class of multitype branching processes with binary family trees\",\"authors\":\"N. Daskalova\",\"doi\":\"10.1080/08898480.2017.1348723\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT When proliferating cells are counted in several independent colonies at some time points, the maximum likelihood estimates of the parameters of the multitype branching process are obtained trough an expectation maximization algorithm. In the case of an offspring distribution governed by a Markov branching process with binary family trees, this method, relying then on a partial knowledge of the tree, yields the same estimates as those computed with the complete knowledge of the tree.\",\"PeriodicalId\":49859,\"journal\":{\"name\":\"Mathematical Population Studies\",\"volume\":\"24 1\",\"pages\":\"246 - 256\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2017-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/08898480.2017.1348723\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematical Population Studies\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1080/08898480.2017.1348723\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"DEMOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Population Studies","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/08898480.2017.1348723","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
Expectation maximization estimates of the offspring probabilities in a class of multitype branching processes with binary family trees
ABSTRACT When proliferating cells are counted in several independent colonies at some time points, the maximum likelihood estimates of the parameters of the multitype branching process are obtained trough an expectation maximization algorithm. In the case of an offspring distribution governed by a Markov branching process with binary family trees, this method, relying then on a partial knowledge of the tree, yields the same estimates as those computed with the complete knowledge of the tree.
期刊介绍:
Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions.
The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.