Weak Convergence of Stochastic Processes : : With Applications to Statistical Limit Theorems / / Vidyadhar S. Mandrekar.

• Superior document: Title is part of eBook package: De Gruyter DG Plus eBook-Package 2016
• VerfasserIn: Mandrekar, Vidyadhar S.,
• Place / Publishing House: Berlin ;, Boston : : De Gruyter, , [2016]; ©2016
• Year of Publication: 2016
• Language: English
• Series: De Gruyter Textbook
• Physical Description: 1 online resource (VI, 142 p.)
• Other title: Frontmatter --; Contents --; 1. Weak convergence of stochastic processes --; 2. Weak convergence in metric spaces --; 3. Weak convergence on C[0, 1] and D[0,∞) --; 4. Central limit theorem for semi-martingales and applications --; 5. Central limit theorems for dependent random variables --; 6. Empirical process --; Bibliography
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9783110476316; 9783110701005; 9783110485103; 9783110485288
• DOI: 10.1515/9783110476316
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: Vidyadhar S. Mandrekar.

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