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SUMMARY:A Bayesian nonparametric approach for the rare type problem - Giul
 ia Cereda (Université de Lausanne\; Universiteit Leiden)
DTSTART:20161111T094500Z
DTEND:20161111T103000Z
UID:TALK68942@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>Co-author: Richard Gill (Leiden University) <br></span> 
  <br>The evaluation of a match between the DNA profile of a stain found on
  a crime  scene and that of a suspect (previously identified) involves the
  use of the  unknown parameter p=(p1\, p2\, ...)\, (the ordered vector whi
 ch represents the  proportions of the different DNA profiles in the popula
 tion of potential donors)  and the names of the different DNA types. <br> 
 <br>We propose a Bayesian nonparametric method which considers p as the  r
 ealization of a random variable P distributed according to the two-paramet
 er  Poisson Dirichlet and discard information about DNA types. <br> <span>
 <br>The ultimate goal of this model is to evaluate DNA matches in the rare
  type  case\, that is the situation in which the suspect&#39\;s profile\, 
 matching the crime  stain profile\, is not one of those in the database of
  reference. This situation  is so problematic that has been called &ldquo\
 ;the fundamental problem of forensic  mathematics&rdquo\; by Charles Brenn
 er.&nbsp\;</span>
LOCATION:Seminar Room 1\, Newton Institute
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