Multidimensional Stationary Time Series

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Multidimensional Stationary Time Series

Author : Marianna Bolla
Publisher : CRC Press
ISBN 13 : 1000392392
Total Pages : 318 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Multidimensional Stationary Time Series by : Marianna Bolla

Download or read book Multidimensional Stationary Time Series written by Marianna Bolla and published by CRC Press. This book was released on 2021-04-29 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a brief survey of the theory of multidimensional (multivariate), weakly stationary time series, with emphasis on dimension reduction and prediction. Understanding the covered material requires a certain mathematical maturity, a degree of knowledge in probability theory, linear algebra, and also in real, complex and functional analysis. For this, the cited literature and the Appendix contain all necessary material. The main tools of the book include harmonic analysis, some abstract algebra, and state space methods: linear time-invariant filters, factorization of rational spectral densities, and methods that reduce the rank of the spectral density matrix. Serves to find analogies between classical results (Cramer, Wold, Kolmogorov, Wiener, Kálmán, Rozanov) and up-to-date methods for dimension reduction in multidimensional time series Provides a unified treatment for time and frequency domain inferences by using machinery of complex and harmonic analysis, spectral and Smith--McMillan decompositions. Establishes analogies between the time and frequency domain notions and calculations Discusses the Wold's decomposition and the Kolmogorov's classification together, by distinguishing between different types of singularities. Understanding the remote past helps us to characterize the ideal situation where there is a regular part at present. Examples and constructions are also given Establishes a common outline structure for the state space models, prediction, and innovation algorithms with unified notions and principles, which is applicable to real-life high frequency time series It is an ideal companion for graduate students studying the theory of multivariate time series and researchers working in this field.

Elements of Multivariate Time Series Analysis

Author : Gregory C. Reinsel
Publisher : Springer Science & Business Media
ISBN 13 : 146840198X
Total Pages : 278 pages
Book Rating : 4.4/5 (684 download)

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Book Synopsis Elements of Multivariate Time Series Analysis by : Gregory C. Reinsel

Download or read book Elements of Multivariate Time Series Analysis written by Gregory C. Reinsel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of methods of time series analysis in the study of multivariate time series has become of increased interest in recent years. Although the methods are rather well developed and understood for univarjate time series analysis, the situation is not so complete for the multivariate case. This book is designed to introduce the basic concepts and methods that are useful in the analysis and modeling of multivariate time series, with illustrations of these basic ideas. The development includes both traditional topics such as autocovariance and auto correlation matrices of stationary processes, properties of vector ARMA models, forecasting ARMA processes, least squares and maximum likelihood estimation techniques for vector AR and ARMA models, and model checking diagnostics for residuals, as well as topics of more recent interest for vector ARMA models such as reduced rank structure, structural indices, scalar component models, canonical correlation analyses for vector time series, multivariate unit-root models and cointegration structure, and state-space models and Kalman filtering techniques and applications. This book concentrates on the time-domain analysis of multivariate time series, and the important subject of spectral analysis is not considered here. For that topic, the reader is referred to the excellent books by Jenkins and Watts (1968), Hannan (1970), Priestley (1981), and others.

Advances in Distribution Theory, Order Statistics, and Inference

Author : N. Balakrishnan
Publisher : Springer Science & Business Media
ISBN 13 : 0817644873
Total Pages : 515 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis Advances in Distribution Theory, Order Statistics, and Inference by : N. Balakrishnan

Download or read book Advances in Distribution Theory, Order Statistics, and Inference written by N. Balakrishnan and published by Springer Science & Business Media. This book was released on 2007-10-23 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to honor the fundamental contributions to many different areas of statistics made by Barry Arnold. Distinguished and active researchers highlight some of the recent developments in statistical distribution theory, order statistics and their properties, as well as inferential methods associated with them. Applications to survival analysis, reliability, quality control, and environmental problems are emphasized.

Statistical Analysis of Stationary Time Series

Author : Ulf Grenander
Publisher : American Mathematical Soc.
ISBN 13 : 0821844377
Total Pages : 312 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Statistical Analysis of Stationary Time Series by : Ulf Grenander

Download or read book Statistical Analysis of Stationary Time Series written by Ulf Grenander and published by American Mathematical Soc.. This book was released on 2008-05 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in the terminology of the theoretical statistician, this book presents an approach to time series analysis. It presents a unified treatment of methods that are being used in the physical sciences and technology.

Time Series Analysis

Author : William W. S. Wei
Publisher : Addison-Wesley Longman
ISBN 13 :
Total Pages : 648 pages
Book Rating : 4.:/5 (318 download)

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Book Synopsis Time Series Analysis by : William W. S. Wei

Download or read book Time Series Analysis written by William W. S. Wei and published by Addison-Wesley Longman. This book was released on 2006 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications. Overview. Fundamental Concepts. Stationary Time Series Models. Nonstationary Time Series Models. Forecasting. Model Identification. Parameter Estimation, Diagnostic Checking, and Model Selection. Seasonal Time Series Models. Testing for a Unit Root. Intervention Analysis and Outlier Detection. Fourier Analysis. Spectral Theory of Stationary Processes. Estimation of the Spectrum. Transfer Function Models. Time Series Regression and GARCH Models. Vector Time Series Models. More on Vector Time Series. State Space Models and the Kalman Filter. Long Memory and Nonlinear Processes. Aggregation and Systematic Sampling in Time Series. For all readers interested in time series analysis.

Time Series Models

Author : Manfred Deistler
Publisher : Springer Nature
ISBN 13 : 3031132130
Total Pages : 213 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Time Series Models by : Manfred Deistler

Download or read book Time Series Models written by Manfred Deistler and published by Springer Nature. This book was released on 2022-10-21 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a self-contained presentation of the theory and models of time series analysis. Putting an emphasis on weakly stationary processes and linear dynamic models, it describes the basic concepts, ideas, methods and results in a mathematically well-founded form and includes numerous examples and exercises. The first part presents the theory of weakly stationary processes in time and frequency domain, including prediction and filtering. The second part deals with multivariate AR, ARMA and state space models, which are the most important model classes for stationary processes, and addresses the structure of AR, ARMA and state space systems, Yule-Walker equations, factorization of rational spectral densities and Kalman filtering. Finally, there is a discussion of Granger causality, linear dynamic factor models and (G)ARCH models. The book provides a solid basis for advanced mathematics students and researchers in fields such as data-driven modeling, forecasting and filtering, which are important in statistics, control engineering, financial mathematics, econometrics and signal processing, among other subjects.

Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences

Author : Maksym Luz
Publisher : John Wiley & Sons
ISBN 13 : 1786305038
Total Pages : 308 pages
Book Rating : 4.7/5 (863 download)

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Book Synopsis Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences by : Maksym Luz

Download or read book Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences written by Maksym Luz and published by John Wiley & Sons. This book was released on 2019-12-12 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation of Stochastic Processes is intended for researchers in the field of econometrics, financial mathematics, statistics or signal processing. This book gives a deep understanding of spectral theory and estimation techniques for stochastic processes with stationary increments. It focuses on the estimation of functionals of unobserved values for stochastic processes with stationary increments, including ARIMA processes, seasonal time series and a class of cointegrated sequences. Furthermore, this book presents solutions to extrapolation (forecast), interpolation (missed values estimation) and filtering (smoothing) problems based on observations with and without noise, in discrete and continuous time domains. Extending the classical approach applied when the spectral densities of the processes are known, the minimax method of estimation is developed for a case where the spectral information is incomplete and the relations that determine the least favorable spectral densities for the optimal estimations are found.

Multiple Time Series

Author : Edward James Hannan
Publisher : John Wiley & Sons
ISBN 13 : 0470317132
Total Pages : 552 pages
Book Rating : 4.4/5 (73 download)

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Book Synopsis Multiple Time Series by : Edward James Hannan

Download or read book Multiple Time Series written by Edward James Hannan and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley Series in Probability and Statistics is a collection of topics of current research interests in both pure and applied statistics and probability developments in the field and classical methods. This series provides essential and invaluable reading for all statisticians, whether in academia, industry, government, or research.

Singular Spectrum Analysis for Time Series

Author : Nina Golyandina
Publisher : Springer Science & Business Media
ISBN 13 : 3642349137
Total Pages : 126 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Singular Spectrum Analysis for Time Series by : Nina Golyandina

Download or read book Singular Spectrum Analysis for Time Series written by Nina Golyandina and published by Springer Science & Business Media. This book was released on 2013-01-19 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA seeks to decompose the original series into a sum of a small number of interpretable components such as trend, oscillatory components and noise. It is based on the singular value decomposition of a specific matrix constructed upon the time series. Neither a parametric model nor stationarity are assumed for the time series. This makes SSA a model-free method and hence enables SSA to have a very wide range of applicability. The present book is devoted to the methodology of SSA and shows how to use SSA both safely and with maximum effect. Potential readers of the book include: professional statisticians and econometricians, specialists in any discipline in which problems of time series analysis and forecasting occur, specialists in signal processing and those needed to extract signals from noisy data, and students taking courses on applied time series analysis.

Time Series: Theory and Methods

Author : Peter J. Brockwell
Publisher : Springer Science & Business Media
ISBN 13 : 1489900047
Total Pages : 532 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Time Series: Theory and Methods by : Peter J. Brockwell

Download or read book Time Series: Theory and Methods written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: We have attempted in this book to give a systematic account of linear time series models and their application to the modelling and prediction of data collected sequentially in time. The aim is to provide specific techniques for handling data and at the same time to provide a thorough understanding of the mathematical basis for the techniques. Both time and frequency domain methods are discussed but the book is written in such a way that either approach could be emphasized. The book is intended to be a text for graduate students in statistics, mathematics, engineering, and the natural or social sciences. It has been used both at the M. S. level, emphasizing the more practical aspects of modelling, and at the Ph. D. level, where the detailed mathematical derivations of the deeper results can be included. Distinctive features of the book are the extensive use of elementary Hilbert space methods and recursive prediction techniques based on innovations, use of the exact Gaussian likelihood and AIC for inference, a thorough treatment of the asymptotic behavior of the maximum likelihood estimators of the coefficients of univariate ARMA models, extensive illustrations of the tech niques by means of numerical examples, and a large number of problems for the reader. The companion diskette contains programs written for the IBM PC, which can be used to apply the methods described in the text.

Advance Trends in Soft Computing

Author : Mo Jamshidi
Publisher : Springer
ISBN 13 : 3319036742
Total Pages : 464 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Advance Trends in Soft Computing by : Mo Jamshidi

Download or read book Advance Trends in Soft Computing written by Mo Jamshidi and published by Springer. This book was released on 2013-11-18 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the proceedings of the 3rd World Conference on Soft Computing (WCSC), which was held in San Antonio, TX, USA, on December 16-18, 2013. It presents start-of-the-art theory and applications of soft computing together with an in-depth discussion of current and future challenges in the field, providing readers with a 360 degree view on soft computing. Topics range from fuzzy sets, to fuzzy logic, fuzzy mathematics, neuro-fuzzy systems, fuzzy control, decision making in fuzzy environments, image processing and many more. The book is dedicated to Lotfi A. Zadeh, a renowned specialist in signal analysis and control systems research who proposed the idea of fuzzy sets, in which an element may have a partial membership, in the early 1960s, followed by the idea of fuzzy logic, in which a statement can be true only to a certain degree, with degrees described by numbers in the interval [0,1]. The performance of fuzzy systems can often be improved with the help of optimization techniques, e.g. evolutionary computation, and by endowing the corresponding system with the ability to learn, e.g. by combining fuzzy systems with neural networks. The resulting “consortium” of fuzzy, evolutionary, and neural techniques is known as soft computing and is the main focus of this book.

Correlation Theory of Stationary and Related Random Functions

Author : A.M. Yaglom
Publisher : Springer Science & Business Media
ISBN 13 : 1461246288
Total Pages : 267 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Correlation Theory of Stationary and Related Random Functions by : A.M. Yaglom

Download or read book Correlation Theory of Stationary and Related Random Functions written by A.M. Yaglom and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. This theory is a significant part of modern probability theory and offers both intrinsic mathematical interest and many concrete and practical applications. Stationary random functions arise in connection with stationary time series which are so important in many areas of engineering and other applications. This book presents the theory in such a way that it can be understood by readers without specialized mathematical backgrounds, requiring only the knowledge of elementary calculus. The first volume in this two-volume exposition contains the main theory; the supplementary notes and references of the second volume consist of detailed discussions of more specialized questions, some more additional material (which assumes a more thorough mathematical background than the rest of the book) and numerous references to the extensive literature.

The Analysis of Multiple Time-series

Author : M. H. Quenouille
Publisher :
ISBN 13 :
Total Pages : 122 pages
Book Rating : 4.3/5 (2 download)

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Book Synopsis The Analysis of Multiple Time-series by : M. H. Quenouille

Download or read book The Analysis of Multiple Time-series written by M. H. Quenouille and published by . This book was released on 1957 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Multiple Time Series Analysis

Author : Helmut Lütkepohl
Publisher : Springer Science & Business Media
ISBN 13 : 3662026910
Total Pages : 556 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Introduction to Multiple Time Series Analysis by : Helmut Lütkepohl

Download or read book Introduction to Multiple Time Series Analysis written by Helmut Lütkepohl and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Modern Multidimensional Scaling

Author : Ingwer Borg
Publisher : Springer Science & Business Media
ISBN 13 : 1475727119
Total Pages : 469 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Modern Multidimensional Scaling by : Ingwer Borg

Download or read book Modern Multidimensional Scaling written by Ingwer Borg and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multidimensional scaling (MDS) is a technique for the analysis of similarity or dissimilarity data on a set of objects. Such data may be intercorrelations of test items, ratings of similarity on political candidates, or trade indices for a set of countries. MDS attempts to model such data as distances among points in a geometric space. The main reason for doing this is that one wants a graphical display of the structure of the data, one that is much easier to understand than an array of numbers and, moreover, one that displays the essential information in the data, smoothing out noise. There are numerous varieties of MDS. Some facets for distinguishing among them are the particular type of geometry into which one wants to map the data, the mapping function, the algorithms used to find an optimal data representation, the treatment of statistical error in the models, or the possibility to represent not just one but several similarity matrices at the same time. Other facets relate to the different purposes for which MDS has been used, to various ways of looking at or "interpreting" an MDS representation, or to differences in the data required for the particular models. In this book, we give a fairly comprehensive presentation of MDS. For the reader with applied interests only, the first six chapters of Part I should be sufficient. They explain the basic notions of ordinary MDS, with an emphasis on how MDS can be helpful in answering substantive questions.

Time Series

Author : David R. Brillinger
Publisher : SIAM
ISBN 13 : 0898715016
Total Pages : 556 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Time Series by : David R. Brillinger

Download or read book Time Series written by David R. Brillinger and published by SIAM. This book was released on 2001-09-01 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals.

Multivariate Time Series Analysis and Applications

Author : William W. S. Wei
Publisher : John Wiley & Sons
ISBN 13 : 1119502853
Total Pages : 536 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Multivariate Time Series Analysis and Applications by : William W. S. Wei

Download or read book Multivariate Time Series Analysis and Applications written by William W. S. Wei and published by John Wiley & Sons. This book was released on 2019-03-18 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the field Following the highly successful and much lauded book, Time Series Analysis—Univariate and Multivariate Methods, this new work by William W.S. Wei focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series. With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by bestselling author and leading expert in the field Covers topics not yet explored in current multivariate books Features classroom tested material Written specifically for time series courses Multivariate Time Series Analysis and its Applications is designed for an advanced time series analysis course. It is a must-have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.