Elements of modern asymptotic theory with statistical applications

Probability and measure random variables and distributions in statistics concepts of asymptotic convergence further asymptotic theory with applications in regression likelihood and associated concepts maximum likelihood and asymptotic theory metric spaces and stochastic processes Brownian motion and weak convergence applications of weak convergence dependent random variables and mixing dependent sequences and martingales.