Weak Convergence of Stochastic Processes: With Applications to Statistical Limit Theorems Contributor(s): Mandrekar, Vidyadhar S. (Author) |
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ISBN: 3110475421 ISBN-13: 9783110475425 Publisher: de Gruyter
WE WILL NOT BE UNDERSOLD! Click here for our low price guarantee Binding Type: Paperback - See All Available Formats & Editions Published: September 2016 Click for more in this series: de Gruyter Textbook |
Additional Information |
BISAC Categories: - Mathematics | Probability & Statistics - Stochastic Processes |
Series: de Gruyter Textbook |
Physical Information: 0.4" H x 6.7" W x 9.4" L (0.65 lbs) 148 pages |
Features: Bibliography |
Descriptions, Reviews, Etc. |
Publisher Description: 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 |
Contributor Bio(s): Mandrekar, Vidyadhar S.: - Vidyadhar Mandrekar, Michigan State University, USA. |
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