The purpose of this book is to present results on the subject of weak convergence in function spaces to study invariance principles in statistical applications to dependent random variables, U-statistics, censor data analysis. Different techniques, formerly available only in a broad range of literature, are for the first time presented here in a self-contained fashion.
Contents:
Weak convergence of stochastic processes
Weak convergence in metric spaces
Weak convergence on C[0, 1] and D[0,8)
Central limit theorem for semi-martingales and applications
Central limit theorems for dependent random variables
Empirical process
Bibliography
Reihe
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
US School Grade: From College Freshman to College Senior
Dateigröße
ISBN-13
978-3-11-047545-6 (9783110475456)
Schweitzer Klassifikation
Vidyadhar Mandrekar, Michigan State University, USA.
