Theory And Applications Of Time Series Analysis

Author : Olga Valenzuela,Fernando Rojas,Luis Javier Herrera,Héctor Pomares,Ignacio Rojas
Publisher : Springer Nature
Page : 460 pages
File Size : 48,5 Mb
Release : 2020-11-20
Category : Business & Economics
ISBN : 9783030562199

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Theory and Applications of Time Series Analysis by Olga Valenzuela,Fernando Rojas,Luis Javier Herrera,Héctor Pomares,Ignacio Rojas Pdf

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.

Author : Peter J. Brockwell,Richard A. Davis
Publisher : Springer Science & Business Media
Page : 604 pages
File Size : 44,5 Mb
Release : 1991
Category : Business & Economics
ISBN : 0387974296

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Time Series: Theory and Methods by Peter J. Brockwell,Richard A. Davis Pdf

Here is a systematic account of linear time series models and their application to the modeling and prediction of data collected sequentially in time. It details techniques for handling data and offers a thorough understanding of their mathematical basis.

Author : Robert H. Shumway,David S. Stoffer
Publisher : Unknown
Page : 568 pages
File Size : 45,8 Mb
Release : 2014-01-15
Category : Electronic
ISBN : 1475732627

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Time Series Analysis and Its Applications by Robert H. Shumway,David S. Stoffer Pdf

Author : Björn Schelter,Matthias Winterhalder,Jens Timmer
Publisher : John Wiley & Sons
Page : 514 pages
File Size : 44,7 Mb
Release : 2006-12-13
Category : Science
ISBN : 9783527609512

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Handbook of Time Series Analysis by Björn Schelter,Matthias Winterhalder,Jens Timmer Pdf

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.

Author : Robert H. Shumway,David S. Stoffer
Publisher : Springer Science & Business Media
Page : 560 pages
File Size : 50,6 Mb
Release : 2013-03-14
Category : Mathematics
ISBN : 9781475732610

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Time Series Analysis and Its Applications by Robert H. Shumway,David S. Stoffer Pdf

A balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using non-trivial data illustrate solutions to problems, such as evaluating pain perception experiments using magnetic resonance imaging or monitoring a nuclear test ban treaty. Although designed as a text for graduate level students in statistics and the physical, biological and social sciences, some parts of the book will also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels, and the material has been updated by adding modern developments involving categorical time series analysis and the spectral envelope, multivariate spectral methods, long memory series, nonlinear models, longitudinal data analysis, resampling techniques, ARCH models, stochastic volatility, wavelets and Monte Carlo Markov chain integration methods. The book is supplemented by data and an exploratory time series analysis program ASTSA for Windows that can be downloaded from the Web as freeware.

Author : Robert H. Shumway,David S. Stoffer
Publisher : Springer
Page : 567 pages
File Size : 47,6 Mb
Release : 2017-04-25
Category : Mathematics
ISBN : 9783319524528

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Time Series Analysis and Its Applications by Robert H. Shumway,David S. Stoffer Pdf

The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods. This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book’s website for download, making all the data sets and scripts easy to load into R.

Author : Jonathan D. Cryer,Kung-Sik Chan
Publisher : Springer Science & Business Media
Page : 501 pages
File Size : 51,9 Mb
Release : 2008-03-06
Category : Mathematics
ISBN : 9780387759593

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Time Series Analysis by Jonathan D. Cryer,Kung-Sik Chan Pdf

This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of squares but a calculus-based introduction to statistics is necessary for a thorough understanding of some of the theory. Actual time series data drawn from various disciplines are used throughout the book to illustrate the methodology.

Author : Jose Casals,Alfredo Garcia-Hiernaux,Miguel Jerez,Sonia Sotoca,A. Alexandre Trindade
Publisher : CRC Press
Page : 286 pages
File Size : 55,9 Mb
Release : 2018-09-03
Category : Mathematics
ISBN : 9781315360256

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State-Space Methods for Time Series Analysis by Jose Casals,Alfredo Garcia-Hiernaux,Miguel Jerez,Sonia Sotoca,A. Alexandre Trindade Pdf

The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, aggregation constraints, or missing in-sample values. Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form. After discussing the formulation of the state-space model, the book illustrates the flexibility of the state-space representation and covers the main state estimation algorithms: filtering and smoothing. It then shows how to compute the Gaussian likelihood for unknown coefficients in the state-space matrices of a given model before introducing subspace methods and their application. It also discusses signal extraction, describes two algorithms to obtain the VARMAX matrices corresponding to any linear state-space model, and addresses several issues relating to the aggregation and disaggregation of time series. The book concludes with a cross-sectional extension to the classical state-space formulation in order to accommodate longitudinal or panel data. Missing data is a common occurrence here, and the book explains imputation procedures necessary to treat missingness in both exogenous and endogenous variables. Web Resource The authors’ E4 MATLAB® toolbox offers all the computational procedures, administrative and analytical functions, and related materials for time series analysis. This flexible, powerful, and free software tool enables readers to replicate the practical examples in the text and apply the procedures to their own work.

Author : Randal Douc,Eric Moulines,David Stoffer
Publisher : CRC Press
Page : 548 pages
File Size : 52,9 Mb
Release : 2014-01-06
Category : Mathematics
ISBN : 9781466502345

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Nonlinear Time Series by Randal Douc,Eric Moulines,David Stoffer Pdf

This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary approaches. They discuss the main limit theorems for Markov chains, useful inequalities, statistical techniques to infer model parameters, and GLMs. Moving on to HMM models, the book examines filtering and smoothing, parametric and nonparametric inference, advanced particle filtering, and numerical methods for inference.

Author : Olga Valenzuela,Fernando Rojas,Luis Javier Herrera,Héctor Pomares,Ignacio Rojas
Publisher : Springer Nature
Page : 236 pages
File Size : 40,8 Mb
Release : 2023-12-11
Category : Mathematics
ISBN : 9783031402098

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Theory and Applications of Time Series Analysis by Olga Valenzuela,Fernando Rojas,Luis Javier Herrera,Héctor Pomares,Ignacio Rojas Pdf

This book presents the latest developments in the theory and applications of time series analysis and forecasting. Comprising a selection of refereed papers, it is divided into several parts that address modern theoretical aspects of time series analysis, forecasting and prediction, with applications to various disciplines, including econometrics and energy research. The broad range of topics discussed, including matters of particular relevance for sustainable development, will give readers a modern perspective on the subject. The included contributions were originally presented at the 8th International Conference on Time Series and Forecasting, ITISE 2022, held in Gran Canaria, Spain, June 27-30, 2022. 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.

Author : Robert Alan Yaffee,Monnie McGee
Publisher : Elsevier
Page : 555 pages
File Size : 42,8 Mb
Release : 2000-05-12
Category : Mathematics
ISBN : 9780080478708

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An Introduction to Time Series Analysis and Forecasting by Robert Alan Yaffee,Monnie McGee Pdf

Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two popular statistical packages--SAS and SPSS. The text examines moving average, exponential smoothing, Census X-11 deseasonalization, ARIMA, intervention, transfer function, and autoregressive error models and has brief discussions of ARCH and GARCH models. The book features treatments of forecast improvement with regression and autoregression combination models and model and forecast evaluation, along with a sample size analysis for common time series models to attain adequate statistical power. The careful linkage of the theoretical constructs with the practical considerations involved in utilizing the statistical packages makes it easy for the user to properly apply these techniques. Describes principal approaches to time series analysis and forecasting Presents examples from public opinion research, policy analysis, political science, economics, and sociology Math level pitched to general social science usage Glossary makes the material accessible for readers at all levels

Author : Olga Valenzuela,Fernando Rojas,Luis Javier Herrera,Héctor Pomares,Ignacio Rojas
Publisher : Springer Nature
Page : 331 pages
File Size : 43,5 Mb
Release : 2023-04-04
Category : Mathematics
ISBN : 9783031141973

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Theory and Applications of Time Series Analysis and Forecasting by Olga Valenzuela,Fernando Rojas,Luis Javier Herrera,Héctor Pomares,Ignacio Rojas Pdf

This book presents a selection of peer-reviewed contributions on the latest developments in time series analysis and forecasting, presented at the 7th International Conference on Time Series and Forecasting, ITISE 2021, held in Gran Canaria, Spain, July 19-21, 2021. It is divided into four parts. The first part addresses general modern methods and theoretical aspects of time series analysis and forecasting, while the remaining three parts focus on forecasting methods in econometrics, time series forecasting and prediction, and numerous other real-world applications. Covering a broad range of topics, the book will give readers a modern perspective on the subject. 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.

Author : Ajoy K. Palit,Dobrivoje Popovic
Publisher : Springer Science & Business Media
Page : 382 pages
File Size : 45,8 Mb
Release : 2006-01-04
Category : Computers
ISBN : 9781846281846

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Computational Intelligence in Time Series Forecasting by Ajoy K. Palit,Dobrivoje Popovic Pdf

Foresight in an engineering business can make the difference between success and failure, and can be vital to the effective control of industrial systems. The authors of this book harness the power of intelligent technologies individually and in combination.

Author : Wilfredo Palma
Publisher : John Wiley & Sons
Page : 616 pages
File Size : 55,9 Mb
Release : 2016-04-29
Category : Mathematics
ISBN : 9781118634233

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Time Series Analysis by Wilfredo Palma Pdf

A modern and accessible guide to the analysis of introductory time series data Featuring an organized and self-contained guide, Time Series Analysis provides a broad introduction to the most fundamental methodologies and techniques of time series analysis. The book focuses on the treatment of univariate time series by illustrating a number of well-known models such as ARMA and ARIMA. Providing contemporary coverage, the book features several useful and newlydeveloped techniques such as weak and strong dependence, Bayesian methods, non-Gaussian data, local stationarity, missing values and outliers, and threshold models. Time Series Analysis includes practical applications of time series methods throughout, as well as: Real-world examples and exercise sets that allow readers to practice the presented methods and techniques Numerous detailed analyses of computational aspects related to the implementation of methodologies including algorithm efficiency, arithmetic complexity, and process time End-of-chapter proposed problems and bibliographical notes to deepen readers’ knowledge of the presented material Appendices that contain details on fundamental concepts and select solutions of the problems implemented throughout A companion website with additional data fi les and computer codes Time Series Analysis is an excellent textbook for undergraduate and beginning graduate-level courses in time series as well as a supplement for students in advanced statistics, mathematics, economics, finance, engineering, and physics. The book is also a useful reference for researchers and practitioners in time series analysis, econometrics, and finance. Wilfredo Palma, PhD, is Professor of Statistics in the Department of Statistics at Pontificia Universidad Católica de Chile. He has published several refereed articles and has received over a dozen academic honors and awards. His research interests include time series analysis, prediction theory, state space systems, linear models, and econometrics. He is the author of Long-Memory Time Series: Theory and Methods, also published by Wiley.

Author : Christopher Chatfield
Publisher : Springer
Page : 277 pages
File Size : 52,6 Mb
Release : 2013-12-01
Category : Mathematics
ISBN : 9781489929259

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The Analysis of Time Series: Theory and Practice by Christopher Chatfield Pdf

Time-series analysis is an area of statistics which is of particular interest at the present time. Time series arise in many different areas, ranging from marketing to oceanography, and the analysis of such series raises many problems of both a theoretical and practical nature. I first became interested in the subject as a postgraduate student at Imperial College, when I attended a stimulating course of lectures on time-series given by Dr. (now Professor) G. M. Jenkins. The subject has fascinated me ever since. Several books have been written on theoretical aspects of time-series analysis. The aim of this book is to provide an introduction to the subject which bridges the gap between theory and practice. The book has also been written to make what is rather a difficult subject as understandable as possible. Enough theory is given to introduce the concepts of time-series analysis and to make the book mathematically interesting. In addition, practical problems are considered so as to help the reader tackle the analysis of real data. The book assumes a knowledge of basic probability theory and elementary statistical inference (see Appendix III). The book can be used as a text for an undergraduate or postgraduate course in time-series, or it can be used for self tuition by research workers. Throughout the book, references are usually given to recent readily accessible books and journals rather than to the original attributive references. Wold's (1965) bibliography contains many time series references published before 1959.