Stationary Processes In Time Series Analysis
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Statistical Analysis Of Stationary Time Series
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Author : Ulf Grenander
language : en
Publisher: American Mathematical Soc.
Release Date : 2008-05
Statistical Analysis Of Stationary Time Series written by Ulf Grenander and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05 with Mathematics categories.
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.
Non Linear And Non Stationary Time Series Analysis
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Author : Maurice Bertram Priestley
language : en
Publisher:
Release Date : 1988
Non Linear And Non Stationary Time Series Analysis written by Maurice Bertram Priestley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Mathematics categories.
Stationary Processes In Time Series Analysis
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Author : Peter James Lambert
language : en
Publisher:
Release Date : 1983
Stationary Processes In Time Series Analysis written by Peter James Lambert and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Time-series analysis categories.
Time Series Models
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Author : Manfred Deistler
language : en
Publisher: Springer Nature
Release Date : 2022-10-21
Time Series Models written by Manfred Deistler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-21 with Mathematics categories.
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.
Time Series Theory And Methods
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Author : Peter J. Brockwell
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Time Series Theory And Methods written by Peter J. Brockwell and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Mathematics categories.
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.
Introduction To Modern Time Series Analysis
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Author : Gebhard Kirchgässner
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-09
Introduction To Modern Time Series Analysis written by Gebhard Kirchgässner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-09 with Business & Economics categories.
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.
The Analysis Of Time Series
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Author : Christopher Chatfield
language : en
Publisher: Chapman & Hall
Release Date : 1984
The Analysis Of Time Series written by Christopher Chatfield and has been published by Chapman & Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Mathematics categories.
Simple descriptive techniques; Probability models for time series; Estimation in the domain; Forecasting; Stationary processes in the frequency domain; Spectral analysis; Bivariate processes; Linear systems.
Applied Time Series Analysis With R
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Author : Wayne A. Woodward
language : en
Publisher: CRC Press
Release Date : 2017-02-17
Applied Time Series Analysis With R written by Wayne A. Woodward and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-17 with Mathematics categories.
Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Analysis with R, Second Edition includes examples across a variety of fields, develops theory, and provides an R-based software package to aid in addressing time series problems in a broad spectrum of fields. The material is organized in an optimal format for graduate students in statistics as well as in the natural and social sciences to learn to use and understand the tools of applied time series analysis. Features Gives readers the ability to actually solve significant real-world problems Addresses many types of nonstationary time series and cutting-edge methodologies Promotes understanding of the data and associated models rather than viewing it as the output of a "black box" Provides the R package tswge available on CRAN which contains functions and over 100 real and simulated data sets to accompany the book. Extensive help regarding the use of tswge functions is provided in appendices and on an associated website. Over 150 exercises and extensive support for instructors The second edition includes additional real-data examples, uses R-based code that helps students easily analyze data, generate realizations from models, and explore the associated characteristics. It also adds discussion of new advances in the analysis of long memory data and data with time-varying frequencies (TVF).
Time Series Analysis
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Author : William W. S. Wei
language : en
Publisher: Addison-Wesley Longman
Release Date : 2006
Time Series Analysis written by William W. S. Wei and has been published by Addison-Wesley Longman this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Time-series analysis categories.
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 Analysis And Forecasting By Example
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Author : Søren Bisgaard
language : en
Publisher: John Wiley & Sons
Release Date : 2011-08-24
Time Series Analysis And Forecasting By Example written by Søren Bisgaard and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-24 with Mathematics categories.
An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in detail and explain the relevant theory while also focusing on the interpretation of results in data analysis. Following a discussion of why autocorrelation is often observed when data is collected in time, subsequent chapters explore related topics, including: Graphical tools in time series analysis Procedures for developing stationary, non-stationary, and seasonal models How to choose the best time series model Constant term and cancellation of terms in ARIMA models Forecasting using transfer function-noise models The final chapter is dedicated to key topics such as spurious relationships, autocorrelation in regression, and multiple time series. Throughout the book, real-world examples illustrate step-by-step procedures and instructions using statistical software packages such as SAS, JMP, Minitab, SCA, and R. A related Web site features PowerPoint slides to accompany each chapter as well as the book's data sets. With its extensive use of graphics and examples to explain key concepts, Time Series Analysis and Forecasting by Example is an excellent book for courses on time series analysis at the upper-undergraduate and graduate levels. it also serves as a valuable resource for practitioners and researchers who carry out data and time series analysis in the fields of engineering, business, and economics.