BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Sequential Quasi-Monte Carlo - Chopin\, N (Centre de Recherche en 
 conomie et Statistique (CREST))
DTSTART:20140422T093000Z
DTEND:20140422T100500Z
UID:TALK52091@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Co-author: Mathieu Gerber (Universit de Lausanne and CREST) \n
 \nWe develop a new class of algorithms\, SQMC (Sequential Quasi-Monte Carl
 o)\, as a variant of SMC (Sequential Monte Carlo) based on low-discrepancy
  points. The complexity of SQMC is O(Nlog N)\, where N is the number of si
 mulations at each iteration\, and its error rate is smaller than the Monte
  Carlo rate O(N^{-1/2}). The only requirement to implement SQMC is the abi
 lity to write the simulation of particle x^n_t given x^n_{t-1} as a determ
 inistic function of x^n_{t-1} and uniform variates. We show that SQMC is a
 menable to the same extensions as standard SMC\, such as forward smoothing
 \, backward smoothing\, unbiased likelihood evaluation\, and so on. In par
 ticular\, SQMC may replace SMC within a PMCMC (particle Markov chain Monte
  Carlo) algorithm. We establish several convergence results. We provide nu
 merical evidence in several difficult scenarios than SQMC significantly ou
 tperforms SMC in terms of approximation error.\n
LOCATION:Seminar Room 1\, Newton Institute
END:VEVENT
END:VCALENDAR