Publications [#70374] of Mark Huber

Papers Accepted

1. M. Huber, Perfect simulation with exponential tails, Random Structures and Algorithms (June, 2007)
   (last updated on 2007/11/24)

   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.