关于非连通图的内在条件自回归模型的一则注释。
A note on intrinsic conditional autoregressive models for disconnected graphs.
作者信息
Freni-Sterrantino Anna, Ventrucci Massimo, Rue Håvard
机构信息
Small Area Health Statistics Unit, Department of Epidemiology and Biostatistics, Imperial College London, United Kingdom.
Department of Statistics, University of Bologna, Bologna, Italy.
出版信息
Spat Spatiotemporal Epidemiol. 2018 Aug;26:25-34. doi: 10.1016/j.sste.2018.04.002. Epub 2018 May 23.
PMID:30390932
Abstract
In this note we discuss (Gaussian) intrinsic conditional autoregressive (CAR) models for disconnected graphs, with the aim of providing practical guidelines for how these models should be defined, scaled and implemented. We show how these suggestions can be implemented in two examples, on disease mapping.
摘要
在本笔记中，我们讨论了用于非连通图的（高斯）内在条件自回归（CAR）模型，目的是为这些模型的定义、缩放和实现提供实用指南。我们展示了如何在疾病映射的两个示例中实施这些建议。
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