Publications [#147643] of Mark Huber

Papers Published

1. M. Huber, Perfect simulation with exponential tails, Random Structures and Algorithms, vol. 33 no. 1 (August, 2008), pp. 29--43, Wiley InterScience
   (last updated on 2008/07/07)

   Abstract:
   Monte Carlo algorithms typically need to generate random variates from a probability distribution described by an unnormalized density or probability mass function. Perfect simulation algorithms generate random variates exactly from these distributions, but have a running time T that is itself an unbounded random variable. This paper shows that commonly used protocols for creating perfect simulation algorithms, such as Coupling From the Past can be used in such a fashion that the running time is unlikely to be very much larger than the expected running time.