摘要翻译：
在经济发展中，往往存在着具有相似经济特征的区域，在这些区域上的经济模型往往具有相似的协变量效应。本文针对空间相关数据，提出了一种贝叶斯聚类回归方法，以便在协变量效应中检测聚类。我们提出的方法基于Dirichlet过程，它提供了一个同时推断聚类数目和聚类结构的概率框架。我们的方法在模拟研究和佐治亚州住房成本数据集的应用中都得到了说明。
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英文标题：
《Heterogeneous Regression Models for Clusters of Spatial Dependent Data》
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作者：
Zhihua Ma, Yishu Xue, Guanyu Hu
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最新提交年份：
2020
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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一级分类：Statistics        统计学
二级分类：Computation        计算
分类描述：Algorithms, Simulation, Visualization
算法、模拟、可视化
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英文摘要：
  In economic development, there are often regions that share similar economic characteristics, and economic models on such regions tend to have similar covariate effects. In this paper, we propose a Bayesian clustered regression for spatially dependent data in order to detect clusters in the covariate effects. Our proposed method is based on the Dirichlet process which provides a probabilistic framework for simultaneous inference of the number of clusters and the clustering configurations. The usage of our method is illustrated both in simulation studies and an application to a housing cost dataset of Georgia.
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PDF链接：
https://arxiv.org/pdf/1907.02212