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\footnotesize
\noindent Statistica Sinica {\bf 15}(2005), 927-943

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\centerline{\large\bf A  NON-MONOTONE CFTP  PERFECT SIMULATION}
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\centerline{\large\bf  METHOD}
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\author{Yuzhi Cai}
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\centerline{\it University of Plymouth}
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\begin{quotation}
\noindent {\it Abstract:}
In this paper, we present a non-monotone {\it coupling from the
past} (CFTP) method for obtaining perfect samples from the
equilibrium distribution of a Markov chain. This  method requires
no  monotone structure that is difficult to define in practice.
We also  apply the non-monotone CFTP method  to general
non-monotone birth-death processes and area-interaction point
processes.\par
\vspace{9pt}
\noindent {\it Key words and phrases:}
Area-interaction point processes, birth-death
 processes,  CFTP, MCMC, monotone, non-monotone,  perfect simulation.\par
\end{quotation}

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