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Weak Convergence of Stochastic Processes : With Applications to Statistical Limit Theorems.

By: Material type: TextTextSeries: De Gruyter Textbook ; 64Publication details: Berlin/Boston, GERMANY : De Gruyter, 2016.Description: 1 online resource (148)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 3110476312
  • 9783110476316
  • 9783110475456
  • 3110475456
Subject(s): Genre/Form: DDC classification:
  • 519.2/3 23
LOC classification:
  • QA273.67 .M29 2016eb
Online resources:
Contents:
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.
Summary: 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.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBSCO Mathematics Available
Total holds: 0

Print version record.

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.

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.

Added to collection customer.56279.3 - Master record variable field(s) change: 072

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