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Physical Applications of Stationary Time-Series

Physical Applications of Stationary Time-Series
Author: Enders A. Robinson
Publisher: Oxford University Press, USA
Total Pages: 313
Release: 1980
Genre: Seismology
ISBN: 9780195205831

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Statistical Analysis of Stationary Time Series

Statistical Analysis of Stationary Time Series
Author: Ulf Grenander
Publisher: American Mathematical Soc.
Total Pages: 312
Release: 2008-05
Genre: Mathematics
ISBN: 0821844377

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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.


Statistical Analysis of Stationary Time Series (Classic Reprint)

Statistical Analysis of Stationary Time Series (Classic Reprint)
Author: Emeritus Professor Division of Applied Mathematics Ulf Grenander
Publisher: Forgotten Books
Total Pages: 308
Release: 2017-10-28
Genre: Mathematics
ISBN: 9781527797307

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Excerpt from Statistical Analysis of Stationary Time Series These schemes have been important in the development of methods for the statistical analysis of time series. They have been used with a varying degree of success to describe many types of phenomena encountered in applications. From the discussion in Chapter 1 it Will be apparent that by using these schemes, it is possible to approximate a large and important class of stationary processes, Viz. The so-called linear processes (see For this to be possible p must take large rather than small values and para meters involved in the scheme must be adjusted adequately. During the last ten years a good deal of work has been devoted to the construction of tests, estimates and confidence intervals appropriate for these schemes. We have described a few of the more important of these results in Chapter 3. In spite of the ingenuity and great theoretical interest of some of these methods, their practical applicability seems to be limited severely by the assumption that the process is a low (usually zero, first or second) order finite parameter scheme. After surveying a good deal of the applied literature devoted to statistical analysis of time series met with in practice, we have come to the following conclusion. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.


Time Series Analysis: Methods and Applications

Time Series Analysis: Methods and Applications
Author: Tata Subba Rao
Publisher: Elsevier
Total Pages: 778
Release: 2012-06-26
Genre: Mathematics
ISBN: 0444538585

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'Handbook of Statistics' is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with volume 30 dealing with time series.


Time Series Analysis: Methods and Applications

Time Series Analysis: Methods and Applications
Author:
Publisher: Elsevier
Total Pages: 777
Release: 2012-05-18
Genre: Mathematics
ISBN: 0444538631

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The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respective areas


Wavelet Methods for Time Series Analysis

Wavelet Methods for Time Series Analysis
Author: Donald B. Percival
Publisher: Cambridge University Press
Total Pages: 628
Release: 2000
Genre: Computers
ISBN: 9780521685085

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This introduction to wavelet analysis 'from the ground level and up', and to wavelet-based statistical analysis of time series focuses on practical discrete time techniques, with detailed descriptions of the theory and algorithms needed to understand and implement the discrete wavelet transforms. Numerous examples illustrate the techniques on actual time series. The many embedded exercises - with complete solutions provided in the Appendix - allow readers to use the book for self-guided study. Additional exercises can be used in a classroom setting. A Web site offers access to the time series and wavelets used in the book, as well as information on accessing software in S-Plus and other languages. Students and researchers wishing to use wavelet methods to analyze time series will find this book essential.


Time Series Analysis and Its Applications

Time Series Analysis and Its Applications
Author: Robert H. Shumway
Publisher: Springer
Total Pages: 567
Release: 2017-04-25
Genre: Mathematics
ISBN: 3319524526

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The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods. This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book’s website for download, making all the data sets and scripts easy to load into R.