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有限LD-QBD过程中的摄动分析及其在流行病模型中的应用。

Perturbation analysis in finite LD-QBD processes and applications to epidemic models.

作者信息

Gómez-Corral A, López-García M

机构信息

Instituto de Ciencias Matemáticas CSIC-UAM-UC3M-UCM, Calle Nicolás Cabrera 13-15, 28049 Madrid, Spain.

Department of Statistics and Operations Research, School of Mathematics, Complutense University of Madrid, 28040 Madrid, Spain.

出版信息

Numer Linear Algebra Appl. 2018 Oct;25(5). doi: 10.1002/nla.2160. Epub 2018 Mar 5.

DOI:10.1002/nla.2160
PMID:30405306
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6218010/
Abstract

In this paper, we adapt arguments from the paper by Caswell [11] to (LD-QBD) processes, which constitute a wide class of structured Markov chains. A LD-QBD process has the special feature that its space of states can be structured by (groups of states), so that a tridiagonal-by-blocks structure is obtained for its infinitesimal generator. For these processes, a number of algorithmic procedures exist in the literature in order to compute several performance measures while exploiting the underlying matrix structure; among others, these measures are related to first-passage times to a certain level (0) and hitting probabilities at this level, the maximum level visited by the process before reaching states of level (0), and the stationary distribution. For the case of a finite number of states, our aim here is to develop analogous algorithms to the ones analyzing these measures, for their perturbation analysis. This approach uses matrix calculus and exploits the specific structure of the infinitesimal generator, which allows us to obtain additional information during the perturbation analysis of the LD-QBD process by dealing with specific matrices carrying probabilistic insights of the dynamics of the process. We illustrate the approach by means of applying multi-type versions of and epidemic models to the spread of antibiotic-sensitive and antibiotic-resistant bacterial strains in a hospital ward.

摘要

在本文中,我们将Caswell [11]论文中的论证方法应用于(LD-QBD)过程,该过程构成了一类广泛的结构化马尔可夫链。LD-QBD过程的特殊之处在于其状态空间可以由(状态组)进行结构化,从而使其无穷小生成元具有分块三对角结构。对于这些过程,文献中存在许多算法程序,以便在利用底层矩阵结构的同时计算多个性能指标;其中,这些指标与到达某个水平(0)的首次通过时间、该水平的击中概率、过程在到达水平(0)的状态之前访问的最大水平以及平稳分布有关。对于有限数量状态的情况,我们在此的目标是开发与分析这些指标的算法类似的算法,用于它们的摄动分析。这种方法使用矩阵微积分并利用无穷小生成元的特定结构,这使我们能够在LD-QBD过程的摄动分析期间通过处理携带过程动态概率见解的特定矩阵来获得额外信息。我们通过将多种类型的传染病模型应用于医院病房中抗生素敏感和耐药细菌菌株的传播来说明该方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/6256708/01f6ba17118f/NLA-25-na-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/6256708/09983792fd27/NLA-25-na-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/6256708/e83d9c0fec36/NLA-25-na-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/6256708/01f6ba17118f/NLA-25-na-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/6256708/09983792fd27/NLA-25-na-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/6256708/e83d9c0fec36/NLA-25-na-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/6256708/01f6ba17118f/NLA-25-na-g003.jpg

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