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Time Series Analysis (eBook)

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eBook Download: EPUB
2016 | 1. Auflage
616 Seiten
John Wiley & Sons (Verlag)
978-1-118-63434-9 (ISBN)

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Time Series Analysis - Wilfredo Palma
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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.

Wilfredo Palma, PhD, is Professor of Statistics in the Department of Statistics at Pontificia Universidad Católica de Chile. Dr. Palma 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.

"This book offers a comprehensive overview of time series analysis...The focus throughout is on methodologies and techniques selected to help the reader develop a working knowledge of practical applications of time series methods... The author manages to incorporate a huge number of topics and his book verges on the encyclopedic...This is a book that would likely be of more use to a serious practitioner of time series analysis than anyone coming fresh to the subject." (Mathematical Association of America 29/03/2017)

"The book has many merits, covering carefully standard basic vocabulary of recently developing time series analysis and presenting lots of illustrative examples of applications that are well organized for the reader who intends to use R libraries for numerical computation" Yuzo Hosoya, MathSciNet, Aug 2017

Erscheint lt. Verlag 28.4.2016
Reihe/Serie Wiley Series in Probability and Statistics
Wiley Series in Probability and Statistics
Sprache englisch
Themenwelt Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Technik
Schlagworte Econometrics • Economics • Finanz- u. Wirtschaftsstatistik • Ökonometrie • Statistics • Statistics for Finance, Business & Economics • Statistik • Time Series • Volkswirtschaftslehre • Zeitreihen • Zeitreihenanalyse
ISBN-10 1-118-63434-9 / 1118634349
ISBN-13 978-1-118-63434-9 / 9781118634349
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