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Multidimensional Stationary Time Series, Bolla, Marianna


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Автор: Bolla, Marianna
Название:  Multidimensional Stationary Time Series
ISBN: 9780367619701
Издательство: Taylor&Francis
Классификация:
ISBN-10: 0367619709
Обложка/Формат: Paperback
Страницы: 270
Вес: 0.45 кг.
Дата издания: 31.05.2023
Иллюстрации: 21 line drawings, black and white; 21 illustrations, black and white
Размер: 234 x 156
Читательская аудитория: Postgraduate, research & scholarly
Подзаголовок: Dimension reduction and prediction
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Поставляется из: Европейский союз


Multidimensional stationary time series

Автор: Bolla, Marianna (budapest University Of Technology And Economics) Szabados, Tamas (budapest University Of Technology And Economics, Hungary)
Название: Multidimensional stationary time series
ISBN: 0367569329 ISBN-13(EAN): 9780367569327
Издательство: Taylor&Francis
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Цена: 19906.00 р.
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Описание: This book gives a brief survey of the theory of multidimensional (multivariate), weakly stationary time series, with emphasis on dimension reduction and prediction.

Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series

Автор: K. Dzhaparidze; Samuel Kotz
Название: Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series
ISBN: 1461293251 ISBN-13(EAN): 9781461293255
Издательство: Springer
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Цена: 16769.00 р.
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Описание: of the spectral density I obtained by applying a certain statistical procedure to the observed values of the variables Xl` . , X , usually depends in n a complicated manner on the cyclic frequency). , are approximated by values of a certain sufficiently simple function 1 = 1

Asymptotic Nonparametric Statistical Analysis of Stationary Time Series

Автор: Daniil Ryabko
Название: Asymptotic Nonparametric Statistical Analysis of Stationary Time Series
ISBN: 3030125637 ISBN-13(EAN): 9783030125639
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Stationarity is a very general, qualitative assumption, that can be assessed on the basis of application specifics. It is thus a rather attractive assumption to base statistical analysis on, especially for problems for which less general qualitative assumptions, such as independence or finite memory, clearly fail. However, it has long been considered too general to be able to make statistical inference. One of the reasons for this is that rates of convergence, even of frequencies to the mean, are not available under this assumption alone. Recently, it has been shown that, while some natural and simple problems, such as homogeneity, are indeed provably impossible to solve if one only assumes that the data is stationary (or stationary ergodic), many others can be solved with rather simple and intuitive algorithms. The latter include clustering and change point estimation among others. In this volume I summarize these results. The emphasis is on asymptotic consistency, since this the strongest property one can obtain assuming stationarity alone. While for most of the problem for which a solution is found this solution is algorithmically realizable, the main objective in this area of research, the objective which is only partially attained, is to understand what is possible and what is not possible to do for stationary time series. The considered problems include homogeneity testing (the so-called two sample problem), clustering with respect to distribution, clustering with respect to independence, change point estimation, identity testing, and the general problem of composite hypotheses testing. For the latter problem, a topological criterion for the existence of a consistent test is presented. In addition, a number of open problems is presented.

Quasi-Stationary Distributions

Автор: Pierre Collet; Servet Mart?nez; Jaime San Mart?n
Название: Quasi-Stationary Distributions
ISBN: 3642428886 ISBN-13(EAN): 9783642428883
Издательство: Springer
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Цена: 12577.00 р.
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Описание: Main concepts of quasi-stationary distributions (QSDs) for killed processes are the focus of the present volume. For diffusions, the killing is at the boundary and for dynamical systems there is a trap. The authors present the QSDs as the ones that allow describing the long-term behavior conditioned to not being killed. Studies in this research area started with Kolmogorov and Yaglom and in the last few decades have received a great deal of attention. The authors provide the exponential distribution property of the killing time for QSDs, present the more general result on their existence and study the process of trajectories that survive forever. For birth-and-death chains and diffusions, the existence of a single or a continuum of QSDs is described. They study the convergence to the extremal QSD and give the classification of the survival process. In this monograph, the authors discuss Gibbs QSDs for symbolic systems and absolutely continuous QSDs for repellers. The findings described are relevant to researchers in the fields of Markov chains, diffusions, potential theory, dynamical systems, and in areas where extinction is a central concept. The theory is illustrated with numerous examples. The volume uniquely presents the distribution behavior of individuals who survive in a decaying population for a very long time. It also provides the background for applications in mathematical ecology, statistical physics, computer sciences, and economics.

Stationary Random Processes Associated with Point Processes

Автор: Tomasz Rolski
Название: Stationary Random Processes Associated with Point Processes
ISBN: 0387905758 ISBN-13(EAN): 9780387905754
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Chapter 2 deals with discrete time theory. The first one is to let the reader get acquainted with the main lines of the theory needed in continuous time without being bothered by tech- nical details. Chapter 3 deals with continuous time theory. Three applications of the continuous time theory are given in Chapter 4.

Bootstrapping Stationary ARMA-GARCH Models

Автор: Kenichi Shimizu
Название: Bootstrapping Stationary ARMA-GARCH Models
ISBN: 3834809926 ISBN-13(EAN): 9783834809926
Издательство: Springer
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Цена: 10760.00 р.
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Описание: Im Jahre 1979 hat Bradley Efron mit seiner Arbeit Bootstrap Methods: Another Look at the Jackknife das Tor zu einem in den vergangenen 30 Jahren intensiv bearbeiteten Forschungsgebiet aufgestoen. Die simulationsbasierte Methode des Bootstraps hat sich in den verschiedensten Bereichen als ein auerordentlich - ?zientes Werkzeug zur Approximation der stochastischen Fluktuation eines Sch- zers um die zu schatzende Groe erwiesen. Prazise Kenntnis dieser stochastischen Fluktuation ist zum Beispiel notwendig, um Kon?denzbereiche fur Schatzer an- geben, die die unbekannte interessierende Groe mit einer vorgegebenen Wa- scheinlichkeit von, sagen wir, 95 oder 99% enthalten. In vielen Fallen und bei korrekter Anwendung ist das Bootstrapverfahren dabei der konkurrierenden und auf der Approximation durch eine Normalverteilung basierenden Methode ub- legen. Die Anzahl der Publikationen im Bereich des Bootstraps ist seit 1979 in einem atemberaubenden Tempo angestiegen. Die wesentliche und im Grunde e- fache Idee des Bootstraps ist die Erzeugung vieler (Pseudo-) Datensatze, die von ihrer wesentlichen stochastischen Struktur dem Ausgangsdatensatz moglichst a- lich sind. Die aktuellen Forschungsinteressen im Umfeld des Bootstraps bewegen sich zu einem groen Teil im Bereich der stochastischen Prozesse. Hier stellt sich die zusatzliche Herausforderung, bei der Erzeugung die Abhangigkeitsstruktur der Ausgangsdaten adaquat zu imitieren. Dabei ist eine prazise Analyse der zugrunde liegenden Situation notwendig, um beurteilen zu konnen, welche Abhangigkei- aspekte fur das Verhalten der Schatzer wesentlich sind und welche nicht, um a- reichend komplexe, aber eben auch moglichst einfache Resamplingvorschlage fur die Erzeugung der Bootstrapdaten entwickeln zu konnen.

Correlation Theory of Stationary and Related Random Functions

Автор: A.M. Yaglom
Название: Correlation Theory of Stationary and Related Random Functions
ISBN: 1461290902 ISBN-13(EAN): 9781461290902
Издательство: Springer
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Цена: 14673.00 р.
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Описание: Correlation Theory of Stationary and Related Random Functions is an elementary introduction to the most important part of the theory dealing only with the first and second moments of these functions.

Stationary stochastic models: an introduction

Автор: Gatto, Riccardo (univ Of Bern, Switzerland)
Название: Stationary stochastic models: an introduction
ISBN: 9811251835 ISBN-13(EAN): 9789811251832
Издательство: World Scientific Publishing
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Цена: 17424.00 р.
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Описание: This volume provides a unified mathematical introduction to stationary time series models and to continuous time stationary stochastic processes. The analysis of these stationary models is carried out in time domain and in frequency domain. It begins with a practical discussion on stationarity, by which practical methods for obtaining stationary data are described. The presented topics are illustrated by numerous examples. Readers will find the following covered in a comprehensive manner:At the end, some selected topics such as stationary random fields, simulation of Gaussian stationary processes, time series for planar directions, large deviations approximations and results of information theory are presented. A detailed appendix containing complementary materials will assist the reader with many technical aspects of the book.

Stationary Stochastic Processes

Автор: Lindgren, Georg
Название: Stationary Stochastic Processes
ISBN: 1466557796 ISBN-13(EAN): 9781466557796
Издательство: Taylor&Francis
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Цена: 15312.00 р.
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The Econometric Analysis of Non-Stationary Spatial Panel Data

Автор: Beenstock, Michael, Felsenstein, Daniel
Название: The Econometric Analysis of Non-Stationary Spatial Panel Data
ISBN: 3030036138 ISBN-13(EAN): 9783030036133
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This monograph deals with spatially dependent non-stationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis.

Stationary Stochastic Processes. (Mn-8)

Автор: Hida Takeyuki
Название: Stationary Stochastic Processes. (Mn-8)
ISBN: 0691648077 ISBN-13(EAN): 9780691648071
Издательство: Wiley
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Цена: 12958.00 р.
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Описание: Encompassing both introductory and more advanced research material, these notes deal with the author`s contributions to stochastic processes and focus on Brownian motion processes and its derivative white noise. Originally published in 1970. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously

Markov Chains

Автор: Kai Lai Chung
Название: Markov Chains
ISBN: 3642620175 ISBN-13(EAN): 9783642620171
Издательство: Springer
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Цена: 16769.00 р.
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Описание: From the reviews:

J. Neveu, 1962 in Zentralblatt f r Mathematik, 92.Band Heft 2, p. 343: "Ce livre crit par l'un des plus minents sp cialistes en la mati re, est un expos tr s d taill de la th orie des processus de Markov d finis sur un espace d nombrable d' tats et homog nes dans le temps (chaines stationnaires de Markov)."

N.Jain, 2008 in Selected Works of Kai Lai Chung, edited by Farid AitSahlia (University of Florida, USA), Elton Hsu (Northwestern University, USA), & Ruth Williams (University of California-San Diego, USA), Chapter 1, p. 15: "This monograph deals with countable state Markov chains in both discrete time (Part I) and continuous time (Part II). ...] Much of Kai Lai's fundamental work in the field is included in this monograph. Here, for the first time, Kai Lai gave a systematic exposition of the subject which includes classification of states, ratio ergodic theorems, and limit theorems for functionals of the chain."


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