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SUMMARY:BSU Seminar: “Quasi Markov Chain Monte Carlo Methods” - Dr. Be
 n Calderhead\, Imperial College London
DTSTART:20180220T143000Z
DTEND:20180220T153000Z
UID:TALK101710@talks.cam.ac.uk
CONTACT:Alison Quenault
DESCRIPTION:Generalised Metropolis-Hastings is a Markov chain Monte Carlo 
 (MCMC) method that was introduced to allow for parallelisation by proposin
 g multiple samples in each iteration\, such that the stationary distributi
 on is still the correct target density.  In this more recent work\, we pro
 ve that the consistency property still holds true when the driving sequenc
 e of pseudo-random numbers is replaced by completely uniformly distributed
  (c.u.d.) numbers.  In essence this allows us to combine ideas from Quasi 
 Monte Carlo with Markov chain Monte Carlo.  In this talk I’ll present id
 eas used to construct this new Monte Carlo method\, along with the results
  of initial numerical simulations that confirm our theoretical result\, an
 d suggest a scaling of order n^-1  as we increase parallelisation instead 
 of the usual n^-1/2 convergence rate of standard MCMC methods.
LOCATION:Large Seminar Room\, 1st Floor\, Institute of Public Health\, Uni
 versity Forvie Site\, Robinson Way\, Cambridge
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