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Perfect simulation of conditionally specified models
Author(s) -
Møller J.
Publication year - 1999
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/1467-9868.00175
Subject(s) - uncountable set , poisson distribution , gibbs sampling , state space , statistical physics , sampling (signal processing) , multivariate statistics , mathematics , binomial (polynomial) , negative binomial distribution , computer science , coupling (piping) , point (geometry) , state (computer science) , discrete mathematics , algorithm , statistics , physics , geometry , mechanical engineering , bayesian probability , countable set , filter (signal processing) , engineering , computer vision
We discuss how the ideas of producing perfect simulations based on coupling from the past for finite state space models naturally extend to multivariate distributions with infinite or uncountable state spaces such as auto‐gamma, auto‐Poisson and autonegative binomial models, using Gibbs sampling in combination with sandwiching methods originally introduced for perfect simulation of point processes.