Limit Theory for Mixing Dependent Random Variables

Author:   Lin Zhengyan ,  Lu Chuanrong
Publisher:   Springer
Edition:   1st ed. Softcover of orig. ed. 1996
Volume:   378
ISBN:  

9789048147489


Pages:   430
Publication Date:   09 December 2010
Format:   Paperback
Availability:   Out of stock   Availability explained
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Limit Theory for Mixing Dependent Random Variables


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Overview

For many practical problems, observations are not independent. In this book, limit behaviour of an important kind of dependent random variables, the so-called mixing random variables, is studied. Many profound results are given, which cover recent developments in this subject, such as basic properties of mixing variables, powerful probability and moment inequalities, weak convergence and strong convergence (approximation), limit behaviour of some statistics with a mixing sample, and many useful tools are provided. Audience: This volume will be of interest to researchers and graduate students in the field of probability and statistics, whose work involves dependent data (variables).

Full Product Details

Author:   Lin Zhengyan ,  Lu Chuanrong
Publisher:   Springer
Imprint:   Springer
Edition:   1st ed. Softcover of orig. ed. 1996
Volume:   378
Dimensions:   Width: 16.00cm , Height: 2.20cm , Length: 24.00cm
Weight:   0.676kg
ISBN:  

9789048147489


ISBN 10:   9048147484
Pages:   430
Publication Date:   09 December 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Preface. Part I: Introduction. 1. Definitions and Basic Inequalities. 2. Moment Estimations of Partial Sums. Part II: Weak Convergence. 3. Weak Convergence for alpha-Mixing Sequences. 4. Weak Convergence for rho-Mixing Sequences. 5. Weak Convergence for phi-Mixing Sequences. 6. Weak Convergence for Mixing Random Fields. 7. The Berry-Esseen Inequality and the Rate of Weak Convergence. Part III: Almost Sure Convergence and Strong Approximations. 8. Laws of Large Numbers and Complete Convergence. 9. Strong Approximations. 10. The Increments of Partial Sums. 11. Strong Approximations for Mixing Random Fields. Part IV: Statistics of a Dependent Sample. 12. Empirical Processes. 13. Convergence of Some Statistics with a Mixing Sample. 14. Strong Approximations for Other Kinds of Dependent Random Variables. Appendix. References. Index.

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