Jeffrey Rosenthal
Department of Statistics , University of Toronto
Scientific, Seminar
UBC Probability Seminar: Jeffrey Rosenthal
Markov chain Monte Carlo (MCMC) algorithms, such as the Metropolis algorithm, are designed to converge to complicated high-dimensional target distributions, to facilitate sampling. The speed of this convergence is essential for practical use. In this...
Scientific, Distinguished Lecture
PIMS Distinguished Chair Lecture Series - Jeffrey Rosenthal
Scientific, Distinguished Lecture
PIMS-UBC Statistics Constance van Eeden Lecture Series: Jeffrey Rosenthal
Markov chain Monte Carlo (MCMC) algorithms, such as the Metropolis Algorithm and the Gibbs Sampler, are an extremely useful and popular method of approximately sampling from complicated probability distributions. Adaptive MCMC attempts to...