Seminar Notice<DIV>
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<DIV>Statistical Laboratory</DIV>
<DIV>Iowa State University</DIV><BR>
<DIV>DATE AND TIME:&nbsp; Friday, January 14, 2005, 4:10 p.m.</DIV><BR>
<DIV>PLACE:&nbsp; 319 Snedecor</DIV><BR>
<DIV>SPEAKER: Yuguo Chen, Institute of Statistics and Decision Sciences, Duke 
University, Durham, North Carolina</DIV><BR>
<DIV>TITLE: Sampling for Conditional Inference on Multiway Tables</DIV><BR><BR>
<DIV>ABSTRACT</DIV><BR><BR>
<DIV>We describe an efficient sequential Monte Carlo method for sampling 
multiway tables with given constraints, which can be used to approximate exact 
conditional inference on contingency tables.&nbsp; An essential feature of our 
new method is that it samples table entries sequentially according to an 
appropriate proposal distribution.&nbsp; The sequential sampling approach 
"divides and conquers" the difficult task of finding an appropriate proposal 
distribution for a multiway table with complex constraints.</DIV><BR>
<DIV>Computational commutative algebra is used to provide conditions that 
guarantee that our method has certain good properties.&nbsp; We apply our method 
to a range of examples from social and medical sciences to demonstrate its 
efficiency in real problems.</DIV><BR>
<DIV>COFFEE:&nbsp; 3:45 p.m., 104 Snedecor Hall</DIV><BR>
<DIV>Seminar schedules and abstracts are available via WWW: <A 
href="http://www.stat.iastate.edu/" 
EUDORA="AUTOURL">http://www.stat.iastate.edu/</A></DIV><BR><BR>
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