Comparing sweep strategies for stochastic relaxation
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Cited by:
- Levine, Richard A. & Casella, George, 2006. "Optimizing random scan Gibbs samplers," Journal of Multivariate Analysis, Elsevier, vol. 97(10), pages 2071-2100, November.
- Yuen, Wai Kong, 2000. "Applications of geometric bounds to the convergence rate of Markov chains on," Stochastic Processes and their Applications, Elsevier, vol. 87(1), pages 1-23, May.
- Rosenthal, Jeffrey S., 1996. "Markov chain convergence: From finite to infinite," Stochastic Processes and their Applications, Elsevier, vol. 62(1), pages 55-72, March.
- Shephard, N. & Pitt, M.K., 1995.
"Likelihood Analysis of Non-Gaussian Parameter-Driven Models,"
Economics Papers
108, Economics Group, Nuffield College, University of Oxford.
- Neil Shephard & Michael K Pitt, 1995. "Likelihood analysis of non-Gaussian parameter driven models," Economics Papers 15 & 108., Economics Group, Nuffield College, University of Oxford.
- Hwang, Chii-Ruey & Sheu, Shuenn-Jyi, 1998. "On the Geometrical Convergence of Gibbs Sampler inRd," Journal of Multivariate Analysis, Elsevier, vol. 66(1), pages 22-37, July.
- Tervonen, Tommi & van Valkenhoef, Gert & Baştürk, Nalan & Postmus, Douwe, 2013. "Hit-And-Run enables efficient weight generation for simulation-based multiple criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 224(3), pages 552-559.
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Keywords
stochastic relaxation sweep strategies products of random affine maps rates of convergence;Statistics
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