TRANSITION MATRIX MONTE CARLO

Robert H. Swendsen (), Brian Diggs, Jian-Sheng Wang, Shing-Te Li, Christopher Genovese and Joseph B. Kadane
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Robert H. Swendsen: Department of Physics, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Brian Diggs: Department of Physics, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Jian-Sheng Wang: Department of Computational Science, National University of Singapore, Singapore 119260, Republic of Singapore
Shing-Te Li: IBM Corp., Bldg. 334, M/S 2A1, 1580 Route 52, Hopewell Junction, NY 12533, New York
Christopher Genovese: Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Joseph B. Kadane: Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA

International Journal of Modern Physics C (IJMPC), 1999, vol. 10, issue 08, 1563-1569

Abstract: Although histogram methods have been extremely effective for analyzing data from Monte Carlo simulations, they do have certain limitations, including the range over which they are valid and the difficulties of combining data from independent simulations. In this paper, we describe a complementary approach to extracting information from Monte Carlo simulations that uses the matrix of transition probabilities. Combining the Transition Matrix with an N-fold way simulation technique produces an extremely flexible and efficient approach to rather general Monte Carlo simulations.

Keywords: Transition matrix; Monte Carlo simulations; Generalized ensembles (search for similar items in EconPapers)
Date: 1999
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DOI: 10.1142/S0129183199001340

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