Weak convergence and empirical processes Aad van der Vaart, Jon Wellner
Publisher: Springer

Wellner (1996): Weak Convergence and Empirical Processes. Weak Convergence Of Measures-Applications In Probability Billingsley.pdf. Consider a large number of indistinguishable particles where the interaction between any two particles is kind of weak and the state dynamics of an individual particle is driven by the mean state of all the other particles. Weak Convergence and Empirical Processes A. His work on uniform central limit theorems (under Richard M. Processes with Applications to Statistics;. Part one reviews stochastic convergence. Of the American Statistical Association, 75, 828–838. ĸ国大百科全书 数学.pdf. Dudley has also made important contributions to mathematical statistics, the theory of weak convergence, relativistic Markov processes, differentiability of nonlinear operators and several other areas of mathematics. A more advanced monograph is "Weak Convergence and Empirical Processes" by Wellner and van der Vaart. For the mean field model, the empirical distribution converges to a deterministic trajectory and the individual queueing process, or more generally the Markov process does not converge. Dudley is a founder of the modern theory of empirical processes in general spaces. ĸ界点理论及其应用 张恭庆.pdf. This book explores weak convergence theory and empirical processes and their applications to many applications in statistics.