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The Analysis of Time Series

The Analysis of Time Series

An Introduction, Sixth Edition

  • Author: Chris Chatfield
  • Publisher: CRC Press
  • ISBN: 9780203491683
  • Category: Mathematics
  • Page: 352
  • View: 445
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Since 1975, The Analysis of Time Series: An Introduction has introduced legions of statistics students and researchers to the theory and practice of time series analysis. With each successive edition, bestselling author Chris Chatfield has honed and refined his presentation, updated the material to reflect advances in the field, and presented interesting new data sets. The sixth edition is no exception. It provides an accessible, comprehensive introduction to the theory and practice of time series analysis. The treatment covers a wide range of topics, including ARIMA probability models, forecasting methods, spectral analysis, linear systems, state-space models, and the Kalman filter. It also addresses nonlinear, multivariate, and long-memory models. The author has carefully updated each chapter, added new discussions, incorporated new datasets, and made those datasets available for download from www.crcpress.com. A free online appendix on time series analysis using R can be accessed at http://people.bath.ac.uk/mascc/TSA.usingR.doc. Highlights of the Sixth Edition: A new section on handling real data New discussion on prediction intervals A completely revised and restructured chapter on more advanced topics, with new material on the aggregation of time series, analyzing time series in finance, and discrete-valued time series A new chapter of examples and practical advice Thorough updates and revisions throughout the text that reflect recent developments and dramatic changes in computing practices over the last few years The analysis of time series can be a difficult topic, but as this book has demonstrated for two-and-a-half decades, it does not have to be daunting. The accessibility, polished presentation, and broad coverage of The Analysis of Time Series make it simply the best introduction to the subject available.

The analysis of time series

The analysis of time series

an introduction

  • Author: Christopher Chatfield
  • Publisher: CRC Press
  • ISBN: N.A
  • Category: Mathematics
  • Page: 268
  • View: 2190
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Simple descriptive techniques; Probability models for series; Estimation in the time domain; Forecasting; Stationary processes in the frequency domain; Spectral analysis; Bivariate processes; Linear systems.

The Analysis of Time Series

The Analysis of Time Series

An Introduction with R

  • Author: Chris Chatfield,Haipeng Xing
  • Publisher: CRC Press
  • ISBN: 1498795641
  • Category: Mathematics
  • Page: 398
  • View: 3841
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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.

The Analysis of Time Series

The Analysis of Time Series

An Introduction, Sixth Edition

  • Author: Christopher Chatfield
  • Publisher: Chapman and Hall/CRC
  • ISBN: N.A
  • Category: Mathematics
  • Page: 304
  • View: 8060
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This book provides a comprehensive introduction to the theory and practice of time series analysis. Topics include:

Introduction to Time Series Analysis and Forecasting

Introduction to Time Series Analysis and Forecasting

  • Author: Douglas C. Montgomery,Cheryl L. Jennings,Murat Kulahci
  • Publisher: John Wiley & Sons
  • ISBN: 1118211502
  • Category: Mathematics
  • Page: 472
  • View: 5662
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An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts. Seven easy-to-follow chapters provide intuitive explanations and in-depth coverage of key forecasting topics, including: Regression-based methods, heuristic smoothing methods, and general time series models Basic statistical tools used in analyzing time series data Metrics for evaluating forecast errors and methods for evaluating and tracking forecasting performance over time Cross-section and time series regression data, least squares and maximum likelihood model fitting, model adequacy checking, prediction intervals, and weighted and generalized least squares Exponential smoothing techniques for time series with polynomial components and seasonal data Forecasting and prediction interval construction with a discussion on transfer function models as well as intervention modeling and analysis Multivariate time series problems, ARCH and GARCH models, and combinations of forecasts The ARIMA model approach with a discussion on how to identify and fit these models for non-seasonal and seasonal time series The intricate role of computer software in successful time series analysis is acknowledged with the use of Minitab, JMP, and SAS software applications, which illustrate how the methods are imple-mented in practice. An extensive FTP site is available for readers to obtain data sets, Microsoft Office PowerPoint slides, and selected answers to problems in the book. Requiring only a basic working knowledge of statistics and complete with exercises at the end of each chapter as well as examples from a wide array of fields, Introduction to Time Series Analysis and Forecasting is an ideal text for forecasting and time series courses at the advanced undergraduate and beginning graduate levels. The book also serves as an indispensable reference for practitioners in business, economics, engineering, statistics, mathematics, and the social, environmental, and life sciences.

Analysis of Time Series Structure

Analysis of Time Series Structure

SSA and Related Techniques

  • Author: Nina Golyandina,Vladimir Nekrutkin,Anatoly A Zhigljavsky
  • Publisher: CRC Press
  • ISBN: 9781420035841
  • Category: Mathematics
  • Page: 320
  • View: 4988
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Over the last 15 years, singular spectrum analysis (SSA) has proven very successful. It has already become a standard tool in climatic and meteorological time series analysis and well known in nonlinear physics and signal processing. However, despite the promise it holds for time series applications in other disciplines, SSA is not widely known among statisticians and econometrists, and although the basic SSA algorithm looks simple, understanding what it does and where its pitfalls lay is by no means simple. Analysis of Time Series Structure: SSA and Related Techniques provides a careful, lucid description of its general theory and methodology. Part I introduces the basic concepts, and sets forth the main findings and results, then presents a detailed treatment of the methodology. After introducing the basic SSA algorithm, the authors explore forecasting and apply SSA ideas to change-point detection algorithms. Part II is devoted to the theory of SSA. Here the authors formulate and prove the statements of Part I. They address the singular value decomposition (SVD) of real matrices, time series of finite rank, and SVD of trajectory matrices. Based on the authors' original work and filled with applications illustrated with real data sets, this book offers an outstanding opportunity to obtain a working knowledge of why, when, and how SSA works. It builds a strong foundation for successfully using the technique in applications ranging from mathematics and nonlinear physics to economics, biology, oceanology, social science, engineering, financial econometrics, and market research.

The Advanced Theory of Statistics: Design and analysis, and time-series

The Advanced Theory of Statistics: Design and analysis, and time-series

  • Author: Maurice George Kendall,Alan Stuart
  • Publisher: Hafner Press
  • ISBN: N.A
  • Category: Mathematics
  • Page: 585
  • View: 4712
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Fourier Analysis of Time Series

Fourier Analysis of Time Series

An Introduction

  • Author: Peter Bloomfield
  • Publisher: John Wiley & Sons
  • ISBN: 0471653993
  • Category: Mathematics
  • Page: 288
  • View: 4541
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A new, revised edition of a yet unrivaled work on frequencydomain analysis Long recognized for his unique focus on frequency domain methodsfor the analysis of time series data as well as for his applied,easy-to-understand approach, Peter Bloomfield brings his well-known1976 work thoroughly up to date. With a minimum of mathematics andan engaging, highly rewarding style, Bloomfield provides in-depthdiscussions of harmonic regression, harmonic analysis, complexdemodulation, and spectrum analysis. All methods are clearlyillustrated using examples of specific data sets, while ampleexercises acquaint readers with Fourier analysis and itsapplications. The Second Edition: Devotes an entire chapter to complex demodulation Treats harmonic regression in two separate chapters Features a more succinct discussion of the fast Fouriertransform Uses S-PLUS commands (replacing FORTRAN) to accommodateprogramming needs and graphic flexibility Includes Web addresses for all time series data used in theexamples An invaluable reference for statisticians seeking to expandtheir understanding of frequency domain methods, FourierAnalysis of Time Series, Second Edition also provides easyaccess to sophisticated statistical tools for scientists andprofessionals in such areas as atmospheric science, oceanography,climatology, and biology.

New Directions in Time Series Analysis

New Directions in Time Series Analysis

  • Author: David Brillinger,Peter Caines,John Geweke,Emanuel Parzen,Murray Rosenblatt,Murad S. Taqqu
  • Publisher: Springer Science & Business Media
  • ISBN: 1461392969
  • Category: Mathematics
  • Page: 382
  • View: 4925
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This IMA Volume in Mathematics and its Applications NEW DIRECTIONS IN TIME SERIES ANALYSIS, PART II is based on the proceedings of the IMA summer program "New Directions in Time Series Analysis. " We are grateful to David Brillinger, Peter Caines, John Geweke, Emanuel Parzen, Murray Rosenblatt, and Murad Taqqu for organizing the program and we hope that the remarkable excitement and enthusiasm of the participants in this interdisciplinary effort are communicated to the reader. A vner Friedman Willard Miller, Jr. PREFACE Time Series Analysis is truly an interdisciplinary field because development of its theory and methods requires interaction between the diverse disciplines in which it is applied. To harness its great potential, strong interaction must be encouraged among the diverse community of statisticians and other scientists whose research involves the analysis of time series data. This was the goal of the IMA Workshop on "New Directions in Time Series Analysis. " The workshop was held July 2-July 27, 1990 and was organized by a committee consisting of Emanuel Parzen (chair), David Brillinger, Murray Rosenblatt, Murad S. Taqqu, John Geweke, and Peter Caines. Constant guidance and encouragement was provided by Avner Friedman, Director of the IMA, and his very helpful and efficient staff. The workshops were organized by weeks. It may be of interest to record the themes that were announced in the IMA newsletter describing the workshop: l.

A Study in the Analysis of Stationary Time Series

A Study in the Analysis of Stationary Time Series

  • Author: Herman O. A. Wold
  • Publisher: N.A
  • ISBN: N.A
  • Category: Probabilities
  • Page: 214
  • View: 8275
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