Operations Research
Stationarity detection in the initial transient problem
ACM Transactions on Modeling and Computer Simulation (TOMACS)
ACM Transactions on Mathematical Software (TOMS)
Exact sampling with coupled Markov chains and applications to statistical mechanics
Proceedings of the seventh international conference on Random structures and algorithms
An interruptible algorithm for perfect sampling via Markov chains
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
The Monty Python method for generating random variables
ACM Transactions on Mathematical Software (TOMS)
SIAM Review
Generating sums in constant average time
WSC '88 Proceedings of the 20th conference on Winter simulation
How to couple from the past using a read-once source of randomness
Random Structures & Algorithms
Algorithm 599: sampling from Gamma and Poisson distributions
ACM Transactions on Mathematical Software (TOMS)
Generating gamma variates by a modified rejection technique
Communications of the ACM
Gamma variate generators with increased shape parameter range
Communications of the ACM
Generating beta variates with nonintegral shape parameters
Communications of the ACM
Extension of Fill's perfect rejection sampling algorithm to general chains
Proceedings of the ninth international conference on on Random structures and algorithms
A hierarchical Bayesian language model based on Pitman-Yor processes
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Random variate generation for exponentially and polynomially tilted stable distributions
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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We consider the problem of the exact simulation of random variables Z that satisfy the distributional identity Z =L VY + (1-V)Z, where V ∈ [0,1] and Y are independent, and =L denotes equality in distribution. Equivalently, Z is the limit of a Markov chain driven by that map. We give an algorithm that can be automated under the condition that we have a source capable of generating independent copies of Y, and that V has a density that can be evaluated in a black-box format. The method uses a doubling trick for inducing coalescence in coupling from the past. Applications include exact samplers for many Dirichlet means, some two-parameter Poisson--Dirichlet means, and a host of other distributions related to occupation times of Bessel bridges that can be described by stochastic fixed point equations.