Rosenthal, Jeffrey S. (Jeffrey Seth) and Rosenthal, Jeffrey S. (Jeffrey Seth)
Probabilities., Measure theory., and Probability measures.
"This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results."--Jacket.
Roberts, Gareth O. and Rosenthal, Jeffrey S. (Jeffrey Seth)
QA, Statistics::Computation, and Statistics::Methodology
Markov chain Monte Carlo (MCMC) algorithms are widely used in statistics, physics, and\ud computer science, to sample from complicated high-dimensional probability distributions. A\ud central question is how quickly the chain converges to the target (stationarity) distribution.\ud In this paper, we consider this question for a particular class of MCMC algorithms,\ud independence samplers (Hastings, 1970; Tierney, 1994).