期刊
COMPUTATIONAL STATISTICS & DATA ANALYSIS
卷 67, 期 -, 页码 68-83出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.csda.2013.04.014
关键词
Approximate Bayesian inference; INLA; Latent Gaussian models
The INLA approach for approximate Bayesian inference for latent Gaussian models has been shown to give fast and accurate estimates of posterior marginals and also to be a valuable tool in practice via the R-package R-INLA. New developments in the R-INLA are formalized and it is shown how these features greatly extend the scope of models that can be analyzed by this interface. The current default method in R-INLA to approximate the posterior marginals of the hyperparameters using only a modest number of evaluations of the joint posterior distribution of the hyperparameters, without any need for numerical integration, is discussed. (c) 2013 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据