Time Series Analysis

<p><b>A modern and accessible guide to the analysis of introductory time series data</b></p> <p>Featuring an organized and self-contained guide, <i>Time Series Analysis </i>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.</p> <p>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. <i>Time Series Analysis </i>includes practical applications of time series methods throughout, as well as:</p> <ul> <li>Real-world examples and exercise sets that allow readers to practice the presented methods and techniques</li> <li>Numerous detailed analyses of computational aspects related to the implementation of methodologies including algorithm efficiency, arithmetic complexity, and process time</li> <li>End-of-chapter proposed problems and bibliographical notes to deepen readers’ knowledge of the presented material</li> <li>Appendices that contain details on fundamental concepts and select solutions of the problems implemented throughout</li> <li>A companion website with additional data fi les and computer codes</li> </ul> <p><i>Time Series Analysis </i>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.</p> <p><b>Wilfredo Palma, PhD,</b> 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 <i>Long-Memory Time Series: Theory and Methods, </i>also published by Wiley.</p>