標題: Parallel chain convergence of time dependent origin-destination matrices with gibbs sampler
作者: Jou, Yow-Jen
Ch, Hsun-Jung
Lan, Chien-Lun
Hsu, Chia-Chun
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: origin-destination;state space model;gibbs sampler;Kalman filter;parallel chain
公開日期: 2006
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.
URI: http://hdl.handle.net/11536/17399
ISBN: 978-90-04-15542-8
ISSN: 1573-4196
期刊: RECENT PROGRESS IN COMPUTATIONAL SCIENCES AND ENGINEERING, VOLS 7A AND 7B
Volume: 7A-B
起始頁: 834
結束頁: 837
顯示於類別:會議論文