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Time-series analysis

Most popular at the top

  • Analysis of Financial Time Seriesby Ruey S. Tsay

    John Wiley & Sons, Inc. 2001; US$ 110.00

    Analysis of Financial Time Series provides a comprehensive and systematic introduction to financial econometric models and their application to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. more...

  • Nonlinear Time Series Analysisby Holger Kantz; Thomas Schreiber

    Cambridge University Press 2003; US$ 69.00

    The time variability of many natural and social phenomena is not well described by standard methods of data analysis. Nonlinear time series analysis uses chaos theory and nonlinear dynamics to understand such seemingly unpredictable behaviour. Results are applied to real data from physics, biology, medicine, and engineering. more...

  • Regression Models for Time Series Analysisby Benjamin Kedem; Konstantinos Fokianos

    John Wiley & Sons, Inc. 2005; US$ 156.00

    A thorough review of the most current regression methods in time series analysis Regression methods have been an integral part of time series analysis for over a century. Recently, new developments have made major strides in such areas as non-continuous data where a linear model is not appropriate. This book introduces the reader to newer developments and more diverse regression models and methods for time series analysis. Accessible to anyone who is familiar with the basic modern concepts of statistical inference, Regression Models for Time Series Analysis provides a much-needed examination of recent statistical developments. Primary among them is the important class of models known as generalized linear models (GLM) which provides, under... more...

  • Applied Nonlinear Time Series Analysisby Michael Small

    World Scientific 2005; US$ 75.40

    Nonlinear time series methods have developed rapidly over a quarter of a century and have reached an advanced state of maturity during the last decade. Implementations of these methods for experimental data are now widely accepted and fairly routine; however, genuinely useful applications remain rare. This book focuses on the practice of applying these methods to solve real problems. To illustrate the usefulness of these methods, a wide variety of physical and physiological systems are considered. The technical tools utilized in this book fall into three distinct, but interconnected areas: quantitative measures of nonlinear dynamics, Monte?Carlo statistical hypothesis testing, and nonlinear modeling. Ten highly detailed applications serve... more...

  • Time-Series Forecastingby Chris Chatfield

    CRC Press 2000; US$ 94.95

    The time-series forecasted methods used in economics, government, industry, and commerce are the subject of this volume, which will be useful to practitioners and researchers in these areas, as well as graduate students. A brief catalog of a wide scope of methods is provided, including the more recent models such as GARCH models, neural networks, a more...

  • Statistical Methods for Spatio-Temporal Systemsby Barbel Finkenstadt

    CRC Press 2006; US$ 89.95

    Provides comprehensive coverage of spatio-temporal models, prevalent in the study of real systems. This book features seven accounts on key features such as point processes, dynamics, modeling, data analysis, Bayesian methods, and geostatistics. It includes real examples, case studies, software, and applications from epidemiology and geology. more...

  • Long-Memory Time Seriesby Wilfredo Palma

    John Wiley & Sons, Inc. 2007; US$ 121.00

    A self-contained, contemporary treatment of the analysis of long-range dependent data Long-Memory Time Series: Theory and Methods provides an overview of the theory and methods developed to deal with long-range dependent data and describes the applications of these methodologies to real-life time series. Systematically organized, it begins with the foundational essentials, proceeds to the analysis of methodological aspects (Estimation Methods, Asymptotic Theory, Heteroskedastic Models, Transformations, Bayesian Methods, and Prediction), and then extends these techniques to more complex data structures. To facilitate understanding, the book: Assumes a basic knowledge of calculus and linear algebra and explains the more advanced statistical... more...

  • Computational Intelligence in Time Series Forecastingby Ajoy K. Palit; Dobrivoje Popovic

    Springer 2006; US$ 189.00

    Deals with the power of intelligent technologies individually and in combination. This book includes examples of the particular systems and processes susceptible to each technique. It is suitable for industrial training purposes, as well as serving as a useful reference material for experimental researchers. more...

  • Future Perfectby Robyn Williams

    Allen & Unwin 2007; US$ 19.62

    With his inimitable and entertaining mix of reportage and feigned indignation, Robyn Williams tackles the future of just about everything - from work and science to god and sex. more...

  • Multiscale Analysis of Complex Time Seriesby Jianbo Gao; Yinhe Cao; Wen-wen Tung; Jing Hu

    John Wiley & Sons, Inc. 2007; US$ 104.95

    The only integrative approach to chaos and random fractal theory Chaos and random fractal theory are two of the most important theories developed for data analysis. Until now, there has been no single book that encompasses all of the basic concepts necessary for researchers to fully understand the ever-expanding literature and apply novel methods to effectively solve their signal processing problems. Multiscale Analysis of Complex Time Series fills this pressing need by presenting chaos and random fractal theory in a unified manner. Adopting a data-driven approach, the book covers: DNA sequence analysis EEG analysis Heart rate variability analysis Neural information processing Network traffic modeling Economic time series analysis And... more...