A general framework for perfect simulation of long memory processes
Probability
2010-04-02 v1
Abstract
In this paper a general approach for the perfect simulation of a stationary process with at most countable state space is outlined. The process is specified through a kernel, prescribing the probability of each state conditional to the whole past history. We follow the seminal paper of Comets, Fernandez and Ferrari, where sufficient conditions for the construction of a certain perfect simulation algorithm have been given. We generalize this approach by defining backward coalescence times for these kind of processes; this allows us to construct perfect simulation algorithms under weaker conditions.
Cite
@article{arxiv.1004.0113,
title = {A general framework for perfect simulation of long memory processes},
author = {Emilio De Santis and Mauro Piccioni},
journal= {arXiv preprint arXiv:1004.0113},
year = {2010}
}
Comments
25 pages