Extension of Fill's perfect rejection sampling algorithm to general chains (Extended abstract)
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[1] Jesper Møller,et al. Perfect Metropolis-Hastings simulation of locally stable point processes , 1999 .
[2] Mark Huber,et al. Exact sampling and approximate counting techniques , 1998, STOC '98.
[3] J. A. Fill. An interruptible algorithm for perfect sampling via Markov chains , 1998 .
[4] Christian P. Robert,et al. On perfect simulation for some mixtures of distributions , 1999, Stat. Comput..
[5] P. Hanlon,et al. A combinatorial description of the spectrum for the Tsetlin library and its generalization to hyperplane arrangements , 1999 .
[6] David Bruce Wilson,et al. How to Get a Perfectly Random Sample from a Generic Markov Chain and Generate a Random Spanning Tree of a Directed Graph , 1998, J. Algorithms.
[7] T. Kamae,et al. Stochastic Inequalities on Partially Ordered Spaces , 1977 .
[8] Jesper Møller,et al. Extensions of Fill's algorithm for perfect simulation , 1999 .
[9] R. Tweedie,et al. Perfect simulation and backward coupling , 1998 .
[10] G. Roberts,et al. An Approach to Diagnosing Total Variation Convergence of MCMC Algorithms , 1997 .
[11] J. Rosenthal. Minorization Conditions and Convergence Rates for Markov Chain Monte Carlo , 1995 .
[12] P. Green,et al. Exact Sampling from a Continuous State Space , 1998 .
[13] Mark Huber,et al. Efficient exact sampling from the Ising model using Swendsen-Wang , 1999, SODA '99.
[14] James Allen Fill,et al. On the Markov Chain for the Move-to-Root Rule for Binary Search Trees , 1995 .
[15] Wilfrid S. Kendall,et al. Perfect simulation in stochastic geometry , 1999, Pattern Recognit..
[16] Persi Diaconis,et al. Iterated Random Functions , 1999, SIAM Rev..
[17] Sylvia Richardson,et al. Markov Chain Monte Carlo in Practice , 1997 .
[18] E. Thönnes. Perfect simulation of some point processes for the impatient user , 1999, Advances in Applied Probability.
[19] L. Tierney. Markov Chains for Exploring Posterior Distributions , 1994 .
[20] Bradley P. Carlin,et al. Markov Chain Monte Carlo conver-gence diagnostics: a comparative review , 1996 .
[21] David B. Wilson. How to couple from the past using a read-once source of randomness , 2000 .
[22] J. Propp,et al. Exact sampling with coupled Markov chains and applications to statistical mechanics , 1996 .
[23] P. Diaconis,et al. Strong Stationary Times Via a New Form of Duality , 1990 .
[24] David Wilson,et al. Coupling from the past: A user's guide , 1997, Microsurveys in Discrete Probability.
[25] David Bruce Wilson,et al. Annotated bibliography of perfectly random sampling with Markov chains , 1997, Microsurveys in Discrete Probability.
[26] Y. Kifer. Ergodic theory of random transformations , 1986 .
[27] Wilfrid S. Kendall,et al. Perfect Simulation for the Area-Interaction Point Process , 1998 .
[28] James Allen Fill,et al. Extension of Fill's perfect rejection sampling algorithm to general chains , 2000, Random Struct. Algorithms.
[29] P. Diaconis,et al. Random walks and hyperplane arrangements , 1998 .
[30] O. Haggstrom,et al. On Exact Simulation of Markov Random Fields Using Coupling from the Past , 1999 .
[31] James Allen Fill,et al. Rates of Convergence for the Move-to-Root Markov Chain for Binary Search Trees , 1995 .
[32] Adrian F. M. Smith,et al. Sampling-Based Approaches to Calculating Marginal Densities , 1990 .
[33] Duncan J. Murdoch,et al. Efficient use of exact samples , 2000, Stat. Comput..
[34] J. A. Fill,et al. Stochastic monotonicity and realizable monotonicity , 2000, math/0005267.
[35] Adrian F. M. Smith,et al. Bayesian computation via the gibbs sampler and related markov chain monte carlo methods (with discus , 1993 .
[36] J. A. Fill. The Move-to-Front Rule: A Case Study for two Perfect Sampling Algorithms , 1998, Probability in the Engineering and Informational Sciences.
[37] J. Møller. Perfect simulation of conditionally specified models , 1999 .
[38] S. Meyn,et al. Computable Bounds for Geometric Convergence Rates of Markov Chains , 1994 .