Weak Convergence of Stochastic Processes: With Applications to Statistical Limit Theorems (de Gruyter Studies in Mathematics) (de Gruyter Textbook)

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 processesWeak convergence in metric spacesWeak convergence on C[0, 1] and D[0,∞)Central limit theorem for semi-martingales and applicationsCentral limit theorems for dependent random variablesEmpirical processBibliography. Read more...

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,∞)
Central limit theorem for semi-martingales and applications
Central limit theorems for dependent random variables
Empirical process
Bibliography

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, ?)
Central limit theorem for semi-martingales and applications
Central limit theorems for dependent random variables
Empirical process
Bibliography

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,∞) Central limit theorem for semi-martingales and applications Central limit theorems for dependent random variables Empirical process Bibliography The purpose of this book is to present results on the subject of weak convergence to study invariance principles in statistical applications. Different techniques, formerly only available in a broad range of literature, are for the first time presented in a self-contained fashion. 1. Weak convergence of stochastic processes 2. Weak convergence in metric spaces 3. Weak convergence on C[0, 1] and D[0,8) 4. Central limit theorem for semi-martingales and applications 5. Central limit theorems for dependent random variables 6. Empirical process.