A shared neighbor conditional autoregressive model for small area spatial data
A shared neighbor conditional autoregressive model for small area spatial data
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DOI：
10.1002/env.2346
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发表时间：
2015-09-01
期刊：
影响因子：
1.7
通讯作者：
Choi, J.
中科院分区：
文献类型：
--
作者：
Lawson, A. B.;Rotejanaprasert, C.;Choi, J.
使用条件自回归（CAR）模型的空间效应是司空见惯的，特别是在处理健康研究中的汇总计数数据时。CAR模型是方便的并且相对容易实现，但是它们在建模相关性方面具有有限的灵活性。我们引入了一个新的CAR模型，可以容纳不同的邻居功能（包括共享邻居）。此外，我们通过模拟来研究该模型与标准CAR模型相比的表现。我们还考虑了应用程序的一个小区域的健康数据的例子。版权所有（c）2015约翰威利父子有限公司
The use of conditional autoregressive (CAR) models for spatial effects is commonplace, especially when dealing with aggregated count data in health studies. CAR models are convenient and relatively easy to implement but suffer from the fact that they have limited flexibility in modeling correlation. We introduce a new CAR model that can accommodate different neighborhood features (including shared neighbors). Further, we examine via simulation how this model performs in comparison with standard CAR models. We also consider the application to a small area health data example. Copyright (c) 2015 John Wiley & Sons, Ltd.