Fill's Algorithm for Absolutely Continuous Stochastically Monotone Kernels
Motoya Machida, Tennessee Technological University
Abstract
Fill, Machida, Murdoch, and Rosenthal (2000) presented
their algorithm and its variants
to extend the perfect sampling algorithm of Fill (1998)
to chains on continuous state spaces.
We consider their algorithm for absolutely continuous stochastically
monotone kernels,
and show the correctness of the algorithm under a set of certain regularity
conditions.
These conditions succeed in relaxing the previously known hypotheses sufficient
for their algorithm to apply.
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