Expectation maximization estimates of the offspring probabilities in a class of multitype branching processes with binary family trees

IF 1.4 3区社会学 Q3 DEMOGRAPHY

Mathematical Population Studies Pub Date : 2017-10-02 DOI:10.1080/08898480.2017.1348723

N. Daskalova

引用次数: 0

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.

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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

摘要当在某些时间点对几个独立菌落中的增殖细胞进行计数时，通过期望最大化算法获得多类型分支过程参数的最大似然估计。在由具有二叉家谱的马尔可夫分支过程控制的子代分布的情况下，该方法依赖于树的部分知识，产生与利用树的完全知识计算的估计相同的估计。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mathematical Population Studies 数学-数学跨学科应用

CiteScore

3.20

自引率

11.10%

发文量

审稿时长

>12 weeks

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.