Parallel chain convergence of time dependent origin-destination matrices with gibbs sampler

Yow-Jen Jou*, Hsun-Jung Ch, Chien Lun Lan, Chia-Chun Hsu

*Corresponding author for this work

研究成果: Chapter同行評審

摘要

An effective method of O-D estimation by the state-space model has been introduced by Jon. Coupled with Gibbs sampler and Kalman filter, the state-space model can generated precious O-D matrices without any prior information while other studies assume that the transition matrix is known or at least approximately known. The Gibbs sampler, a particular type of Markov Chain Monte Carlo method, is one of the iterative simulation methods. To monitor of convergence of this iterative simulation, a parallel chain technique is implemented in this paper. By the numerical example, the convergence of the different chains would be clearly pointed out. The comparison of simulation and real data also shows that satisfying results can be obtained by the model.
原文American English
主出版物標題Recent progress in computational sciences and engineering, vols 7a and 7b
編輯G Maroulis, T Simos
頁面834-+
7A-B
出版狀態Published - 2006
事件 International Conference on Computational Methods in Science and Engineering - Chania, Greece
持續時間: 27 十月 20061 十一月 2007

出版系列

名字 LECTURE SERIES ON COMPUTER AND COMPUTATIONAL SCIENCES
7A-B
ISSN(列印)1573-4196

Conference

Conference International Conference on Computational Methods in Science and Engineering
國家Greece
城市Chania
期間27/10/061/11/07

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