Short Biography:David Aldous is Professor Emeritus in the Statistics Dept at U.C. Berkeley. He is the author of "Probability Approximations via the Poisson Clumping Heuristic" and (with Jim Fill) of a notorious unfinished online work "Reversible Markov Chains and Random Walks … Read more
Introduction to Stein’s method Abstract: In this lecture series I will give a gentle introduction to Stein's method for proving distributional convergence. In 1972 Charles Stein combined Gaussian integration by parts with a certain “noise robustness” property of a sequence … Read more
Existence of MLEs for the parameters of an adjusted linear preferential attachment model of random graphs with covariates In this talk, we consider a variation on the preferential attachment model (PAM) of random graphs with covariates. It is similar to … Read more
Introduction to Stein’s method Abstract: In this lecture series I will give a gentle introduction to Stein's method for proving distributional convergence. In 1972 Charles Stein combined Gaussian integration by parts with a certain “noise robustness” property of a sequence … Read more
Every Statistical Problem is a Missing Data/Causal Inference Problem Across numerous fields of domain science research, challenges arise routinely where data of interest are missing and/or inferences are required regarding, for example, the causal effects of treatments based on observational … Read more
