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Asymptotic Theory of Weakly Dependent Random Processes (Probability Theory and S
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- Sofort-KaufenAsymptotic Theory of Weakly Dependent Random Processes (Probability Theory and S
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Artikelmerkmale
- Artikelzustand
- subject_code
- PBK
- target_audience
- General/trade
- is_adult_product
- false
- edition_number
- 1
- binding
- paperback
- edition
- Softcover reprint of the original 1st ed. 2017
- series_number
- 80
- MPN
- N/A
- batteries_required
- false
- manufacturer
- Springer
- volume
- 80
- Brand
- Springer
- series_title
- Probability Theory and Stochastic Modelling
- number_of_items
- 1
- pages
- 224
- genre
- Probability & statistics
- publication_date
- 2018-07-25T00:00:01Z
- unspsc_code
- 55101500
- batteries_included
- false
- ISBN
- 9783662571910
Über dieses Produkt
Product Identifiers
Publisher
Springer Berlin / Heidelberg
ISBN-10
3662571919
ISBN-13
9783662571910
eBay Product ID (ePID)
2309846490
Product Key Features
Number of Pages
Xviii, 204 Pages
Language
English
Publication Name
Asymptotic Theory of Weakly Dependent Random Processes
Publication Year
2018
Subject
Probability & Statistics / Stochastic Processes, Probability & Statistics / General, Numerical Analysis, System Theory, Mathematical Analysis
Type
Textbook
Subject Area
Mathematics, Science
Series
Probability Theory and Stochastic Modelling Ser.
Format
Trade Paperback
Dimensions
Item Weight
16 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Dewey Edition
23
Series Volume Number
80
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
519.23
Original Language
French
Table Of Content
Introduction.- Variance of partial sums.- Algebraic moments. Elementary exponential inequalities.- Maximal inequalities and strong laws.- Central limit theorems.- Coupling and mixing.- Fuk-Nagaev inequalities, applications.- Empirical distribution functions.- Empirical processes indexed by classes of functions.- Irreducible Markov chains.- Appendices.- References.- Index.
Synopsis
Presenting tools to aid understanding of asymptotic theory and weakly dependent processes, this book is devoted to inequalities and limit theorems for sequences of random variables that are strongly mixing in the sense of Rosenblatt, or absolutely regular. The first chapter introduces covariance inequalities under strong mixing or absolute regularity. These covariance inequalities are applied in Chapters 2, 3 and 4 to moment inequalities, rates of convergence in the strong law, and central limit theorems. Chapter 5 concerns coupling. In Chapter 6 new deviation inequalities and new moment inequalities for partial sums via the coupling lemmas of Chapter 5 are derived and applied to the bounded law of the iterated logarithm. Chapters 7 and 8 deal with the theory of empirical processes under weak dependence. Lastly, Chapter 9 describes links between ergodicity, return times and rates of mixing in the case of irreducible Markov chains. Each chapter ends with a set of exercises. The book is an updated and extended translation of the French edition entitled "Théorie asymptotique des processus aléatoires faiblement dépendants" (Springer, 2000). It will be useful for students and researchers in mathematical statistics, econometrics, probability theory and dynamical systems who are interested in weakly dependent processes.
LC Classification Number
QA273.A1-274.9
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