publication . Conference object . Preprint . 2010

Nested Sampling with Constrained Hamiltonian Monte Carlo

Michael Betancourt; Ali Mohammad-Djafari; Jean-François Bercher; Pierre Bessiére;
Open Access
  • Published: 02 May 2010
  • Publisher: AIP
Abstract
Comment: 15 pages, 4 figures
Subjects
free text keywords: Statistics, Monte Carlo integration, Hybrid Monte Carlo, Markov chain Monte Carlo, symbols.namesake, symbols, Mathematics, Slice sampling, Monte Carlo method in statistical physics, Importance sampling, Rejection sampling, Econometrics, Monte Carlo method, Physics - Data Analysis, Statistics and Probability
Related Organizations

[1] MacKay, D. J. C. (2003) Information Theory, Inference, and Learning Algorithms. Cambridge University Press, New York

[2] Jaynes, E. T. (2003) Probability Theory: The Logic of Science, Cambridge University Press, New York

[3] Skilling, J. (2004) Nested Sampling. In Maximum Entropy and Bayesian methods in science and engineering (ed. G. Erickson, J. T. Rychert, C. R. Smith). AIP Conf. Proc., 735: 395-405. [OpenAIRE]

[4] Sivia, D. S. with Skilling, J. (2006) Data Analysis. Oxford, New York [OpenAIRE]

[5] Feroz, F., Hobson, M. P, Bridges, M. arXiv:0809.3437v1

[6] Brewer, B. J., Partay, L. B., and Csanyi, G. arXiv:0912.2380v1

[7] Bishop, C.M. (2007) Pattern Classification and Machine Learning. Springer, New York

[8] Neal, R. M. MCMC using Hamiltonian http://www.cs.utoronto.ca/~radford/ham-mcmc.abstract.html, 2010. dynamics, March 5,

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publication . Conference object . Preprint . 2010

Nested Sampling with Constrained Hamiltonian Monte Carlo

Michael Betancourt; Ali Mohammad-Djafari; Jean-François Bercher; Pierre Bessiére;