Professor Arnaud Doucet
Biographical: I obtained my PhD from the University of Paris XI (Orsay) in 1997. I previously held academic positions at Cambridge University, Melbourne University, The Institute of Statistical Mathematics in Tokyo and the University of British Columbia where I was a Canada Research Chair in Stochastic Computation.
Bayesian statistics; Stochastic Simulation; Sequential Monte Carlo; Markov Chain Monte Carlo; Time Series.
I am primarily interested in the development and study of novel Monte Carlo methods for inference in complex stochastic models.
A. Doucet, M. K. Pitt, G. Deligiannidis and R . John, Efficient Implementation of Markov chain Monte Carlo when Using an Unbiased Likelihood Estimator, Biometrika, vol. 102, no. 2, pp. 295-313, 2015.
G. G. Poyiadjis, A. Doucet and S.S. Singh, Particle Approximations of the Score and Observed Information Matrix in State-Space Models with Application to Parameter Estimation, Biometrika, vol. 98, no. 1, pp. 65-80, 2011.
C. Andrieu, A. Doucet and R. Holenstein, Particle Markov chain Monte Carlo methods (with discussion), J. Royal Statist. Soc. B, vol. 72, no. 3, pp. 269-342, 2010.
P. Del Moral, A. Doucet and A. Jasra, Sequential Monte Carlo Samplers, J. Royal Statist. Soc. B, vol. 68, no. 3, pp. 411-436, 2006.
Personal homepage: http://www.stats.ox.ac.uk/~doucet/