A Bayesian approach to parameter estimation in HIV dynamical models
A Bayesian approach to parameter estimation in HIV dynamical models
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DOI：
10.1002/sim.1211
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发表时间：
2002-08-15
影响因子：
2
通讯作者：
de Wolf, F
中科院分区：
文献类型：
--
作者：
Putter, H;Heisterkamp, SH;de Wolf, F
在描述HIV感染的数学模型的背景下，我们讨论了贝叶斯建模方法的非线性随机效应估计问题。该模型和数据表现出一些特征，使得普通非线性混合效应模型的使用变得棘手：（i）数据来自同时针对常微分方程系统的隐式数值解拟合的两个房室;（ii）来自一个房室的数据受到删失;（iii）假设一个变量的随机效应来自β分布。我们将展示如何利用贝叶斯框架，将先验知识的一些参数，并结合后验分布的参数，以获得估计的数量的兴趣，从假设的模型。版权所有（C）2002约翰威利父子有限公司
In the context of a mathematical model describing HIV infection, we discuss a Bayesian modelling approach to a non-linear random effects estimation problem. The model and the data exhibit a number of features that make the use of an ordinary non-linear mixed effects model intractable: (i) the data are from two compartments fitted simultaneously against the implicit numerical solution of a system of ordinary differential equations; (ii) data from one compartment are subject to censoring; (iii) random effects for one variable are assumed to be from a beta distribution. We show how the Bayesian framework can be exploited by incorporating prior knowledge on some of the parameters, and by combining the posterior distributions of the parameters to obtain estimates of quantities of interest that follow from the postulated model. Copyright (C) 2002 John Wiley Sons, Ltd.