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Time Series Analysis Univariate And Multivariate Methods
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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.
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.
Book Synopsis Introduction to Time Series and Forecasting by : Peter J. Brockwell
Download or read book Introduction to Time Series and Forecasting written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2006-04-10 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an introduction to time series that emphasizes methods and analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills. Statisticians and students will learn the latest methods in time series and forecasting, along with modern computational models and algorithms.
Book Synopsis A Course in Time Series Analysis by : Daniel Peña
Download or read book A Course in Time Series Analysis written by Daniel Peña and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: Contributions from eleven of the worldâ??s leading figures in time series Shared balance between theory and application Exercise series sets Many real data examples Consistent style and clear, common notation in all contributions 60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor's Manual presenting detailed solutions to all the problems in he book is available upon request from the Wiley editorial department.
Book Synopsis Handbook of Time Series Analysis by : Björn Schelter
Download or read book Handbook of Time Series Analysis written by Björn Schelter and published by John Wiley & Sons. This book was released on 2006-12-13 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides an up-to-date survey of current research topics and applications of time series analysis methods written by leading experts in their fields. It covers recent developments in univariate as well as bivariate and multivariate time series analysis techniques ranging from physics' to life sciences' applications. Each chapter comprises both methodological aspects and applications to real world complex systems, such as the human brain or Earth's climate. Covering an exceptionally broad spectrum of topics, beginners, experts and practitioners who seek to understand the latest developments will profit from this handbook.
Book Synopsis Multivariate Time Series Analysis by : Ruey S. Tsay
Download or read book Multivariate Time Series Analysis written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2013-11-11 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce the presented content • User-friendly R subroutines and research presented throughout to demonstrate modern applications • Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.
Book Synopsis Statistical Analysis by : Sam Kash Kachigan
Download or read book Statistical Analysis written by Sam Kash Kachigan and published by . This book was released on 1986 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic book provides the much needed conceptual explanations of advanced computer-based multivariate data analysis techniques: correlation and regression analysis, factor analysis, discrimination analysis, cluster analysis, multi-dimensional scaling, perceptual mapping, and more. It closes the gap between spiraling technology and its intelligent application, fulfilling the potential of both.
Book Synopsis The Analysis of Time Series by : Chris Chatfield
Download or read book The Analysis of Time Series written by Chris Chatfield and published by CRC Press. This book was released on 2019-04-25 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models. It also presents many examples and implementations of time series models and methods to reflect advances in the field. Highlights of the seventh edition: A new chapter on univariate volatility models A revised chapter on linear time series models A new section on multivariate volatility models A new section on regime switching models Many new worked examples, with R code integrated into the text The book can be used as a textbook for an undergraduate or a graduate level time series course in statistics. The book does not assume many prerequisites in probability and statistics, so it is also intended for students and data analysts in engineering, economics, and finance.
Book Synopsis Time Series Analysis for the Social Sciences by : Janet M. Box-Steffensmeier
Download or read book Time Series Analysis for the Social Sciences written by Janet M. Box-Steffensmeier and published by Cambridge University Press. This book was released on 2014-12-22 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.
Author :Gebhard Kirchgässner Publisher :Springer Science & Business Media ISBN 13 :9783540687351 Total Pages :288 pages Book Rating :4.6/5 (873 download)
Book Synopsis Introduction to Modern Time Series Analysis by : Gebhard Kirchgässner
Download or read book Introduction to Modern Time Series Analysis written by Gebhard Kirchgässner and published by Springer Science & Business Media. This book was released on 2008-08-27 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.
Book Synopsis Time Series Analysis and Its Applications by : Robert H. Shumway
Download or read book Time Series Analysis and Its Applications written by Robert H. Shumway and published by . This book was released on 2014-01-15 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Time Series written by Raquel Prado and published by CRC Press. This book was released on 2010-05-21 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLAB® code, and other material are available on the authors’ websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas.
Book Synopsis Modeling Financial Time Series with S-PLUS by : Eric Zivot
Download or read book Modeling Financial Time Series with S-PLUS written by Eric Zivot and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This Second Edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the "2000 Outstanding Scholars of the 21st Century" by International Biographical Centre.
Book Synopsis Exchange Rate Forecasting: Techniques and Applications by : I. Moosa
Download or read book Exchange Rate Forecasting: Techniques and Applications written by I. Moosa and published by Springer. This book was released on 2016-02-05 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting exchange rates is a variable that preoccupies economists, businesses and governments, being more critical to more people than any other variable. In Exchange Rate Forecasting the author sets out to provide a concise survey of the techniques of forecasting - bringing together the various forecasting methods and applying them to the exchange rate in a highly accessible and readable manner. Highly practical in approach, the book provides an understanding of the techniques of forecasting with an emphasis on its applications and use in business decision-making, such as hedging, speculation, investment, financing and capital budgeting. In addition, the author also considers recent developments in the field, notably neural networks and chaos, again, with easy-to-understand explanations of these "rocket science" areas. The practical approach to forecasting is also reflected in the number of examples that pepper the text, whilst descriptions of some of the software packages that are used in practice to generate forecasts are also provided.
Download or read book Time Series written by Raquel Prado and published by CRC Press. This book was released on 2021-07-27 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Expanded on aspects of core model theory and methodology. • Multiple new examples and exercises. • Detailed development of dynamic factor models. • Updated discussion and connections with recent and current research frontiers.
Book Synopsis Time Series Analysis by State Space Methods by : James Durbin
Download or read book Time Series Analysis by State Space Methods written by James Durbin and published by OUP Oxford. This book was released on 2012-05-03 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series. Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations. Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.
Book Synopsis Theory and Applications of Time Series Analysis by : Olga Valenzuela
Download or read book Theory and Applications of Time Series Analysis written by Olga Valenzuela and published by Springer Nature. This book was released on 2020-11-20 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a selection of peer-reviewed contributions on the latest advances in time series analysis, presented at the International Conference on Time Series and Forecasting (ITISE 2019), held in Granada, Spain, on September 25-27, 2019. The first two parts of the book present theoretical contributions on statistical and advanced mathematical methods, and on econometric models, financial forecasting and risk analysis. The remaining four parts include practical contributions on time series analysis in energy; complex/big data time series and forecasting; time series analysis with computational intelligence; and time series analysis and prediction for other real-world problems. Given this mix of topics, readers will acquire a more comprehensive perspective on the field of time series analysis and forecasting. The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics, statistics and econometrics.
