文章基本信息

标题：GENERALIZED BAYES ESTIMATION OF SPATIAL AUTOREGRESSIVE MODELS
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作者：Anoop Chaturvedi ; Sandeep Mishra
期刊名称：Statistics in Transition
印刷版ISSN：1234-7655
电子版ISSN：2450-0291
出版年度：2019
卷号：20
期号：2
页码：15-31
DOI：10.21307/stattrans-2019-012
出版社：Exeley Inc.
摘要：The spatial autoregressive (SAR) models are widely used in spatial econometrics for analyzing spatial data involving spatial autocorrelation structure. The present paper derives a Generalized Bayes estimator for estimating the parameters of a SAR model. The admissibility and minimaxity properties of the estimator have been discussed. For investigating the finite sample behaviour of the estimator, the results of a simulation study have been presented. The results of the paper are applied to demographic data on total fertility rate for selected Indian states.
关键词：spatial autoregressive model; prior and posterior distributions; generalized Bayes estimator; admissibility and minimaxity; total fertility rate (TFR)