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Arnaud Doucet
Also published under:A. Doucet
Affiliation
Department of Statistics, University of Oxford, Oxford, U.K.
Topic
State-space Model,Almost Surely,Hidden Markov Model,Markov Chain,Optimal Filter,Recursive Estimation,Transition Kernel,Borel Set,Maximum Likelihood Estimation,Model Estimates,Real Numbers,Stochastic Optimization,Asymptotic Properties,Compact Set,Information Theory,Lebesgue Measure,Lipschitz Continuous,Maximum Likelihood,Maximum Likelihood Algorithm,Number Of Papers,Recursive Algorithm,Rest Of The Proof,Statistical Inference,System Identification,Acceptance Probability,Adaptive Components,Analysis Of Properties,Augmented Model,Bayesian Model,Behavior Of Algorithm,Bottom Of Page,Candidate Models,Carrier Frequency,Channel Coefficients,Channel Estimation,Channel Offset,Choice Of Domain,Complexity Measures,Computational Complexity,Discrepancy Measure,Empirical Measures,Entropy Rate,Extended Kalman Filter,Extensive Analysis,Finite State Space,First-order Derivative,Fisher Information Matrix,Gap In The Literature,Gibbs Sampling,Higher-order Derivatives,
Biography
Arnaud Doucet received the Ph.D. degree from University Paris-XI (Orsay) in 1997. He has held ever since faculty positions with The University of Melbourne, Cambridge University, The University of British Columbia, and The Institute of Statistical Mathematics, Tokyo. He joined the Department of Statistics, University of Oxford, where he is currently a Chair Professor. His research interests include computational statistics, Monte Carlo methods, and statistical machine learning.