文章基本信息

标题：Bayesian Reconstruction of Missing Observations
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作者：Shun KATAOKA ; Muneki YASUDA ; Kazuyuki TANAKA 等
期刊名称：Interdisciplinary Information Sciences
印刷版ISSN：1340-9050
电子版ISSN：1347-6157
出版年度：2015
卷号：21
期号：1
页码：11-23
DOI：10.4036/iis.2015.11
出版社：The Editorial Committee of the Interdisciplinary Information Sciences
摘要：We focus on an interpolation method referred to Bayesian reconstruction in this paper. Whereas in standard interpolation methods missing data are interpolated deterministically, in Bayesian reconstruction, missing data are interpolated probabilistically using a Bayesian treatment. In this paper, we address the framework of Bayesian reconstruction and its application to the traffic data reconstruction problem in the field of traffic engineering. In the latter part of this paper, we describe the evaluation of the statistical performance of our Bayesian traffic reconstruction model using a statistical mechanical approach and clarify its statistical behavior.
关键词：Bayesian reconstruction;missing data;traffic data reconstruction;Markov random field;mean-field analysis