Some recent theory of empirical processes indexed by general classes of sets of functions is reviewed. Several of the main results, as well as some of the methods, such as randomization and reduction to Gaussian processes, are described. Applications in asymptotic statistics are illustrated by a few examples. The bootstrap of empirical processes, which enhances the applicability of the theory (as invariance of the limit law is the exception rather than the rule), is also discussed.
"Empirical processes and applications: an overview." Bernoulli 2 (1) 1 - 28, March 1996. https://doi.org/10.3150/bj/1193758786