Spectral Analysis Of Time Series Data
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Spectral Analysis Of Time Series Data
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Author : Rebecca M. Warner
language : en
Publisher: Guilford Press
Release Date : 1998-05-22
Spectral Analysis Of Time Series Data written by Rebecca M. Warner and has been published by Guilford Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-05-22 with Social Science categories.
This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both for researchers and students new to the area and for those who have already collected time-series data but wish to learn new ways of understanding and presenting them. Facilitating the interpretation of observations of behavior, physiology, mood, perceptual threshold, social indicator variables, and other responses, the book focuses on practical applications and requires much less mathematical background than most comparable texts. Using real data sets and currently available software (SPSS for Windows), the author employs extensive examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation, and potential sources of artifact.
The Spectral Analysis Of Time Series
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Author : L. H. Koopmans
language : en
Publisher: Academic Press
Release Date : 2014-05-12
The Spectral Analysis Of Time Series written by L. H. Koopmans and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-12 with Mathematics categories.
The Spectral Analysis of Time Series describes the techniques and theory of the frequency domain analysis of time series. The book discusses the physical processes and the basic features of models of time series. The central feature of all models is the existence of a spectrum by which the time series is decomposed into a linear combination of sines and cosines. The investigator can used Fourier decompositions or other kinds of spectrals in time series analysis. The text explains the Wiener theory of spectral analysis, the spectral representation for weakly stationary stochastic processes, and the real spectral representation. The book also discusses sampling, aliasing, discrete-time models, linear filters that have general properties with applications to continuous-time processes, and the applications of multivariate spectral models. The text describes finite parameter models, the distribution theory of spectral estimates with applications to statistical inference, as well as sampling properties of spectral estimates, experimental design, and spectral computations. The book is intended either as a textbook or for individual reading for one-semester or two-quarter course for students of time series analysis users. It is also suitable for mathematicians or professors of calculus, statistics, and advanced mathematics.
The Spectral Analysis Of Time Series
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Author : Lambert Herman Koopmans
language : en
Publisher:
Release Date : 1974
The Spectral Analysis Of Time Series written by Lambert Herman Koopmans and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974 with Mathematics categories.
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Spectral Analysis For Univariate Time Series
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Author : Donald B. Percival
language : en
Publisher: Cambridge University Press
Release Date : 2020-03-19
Spectral Analysis For Univariate Time Series written by Donald B. Percival and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-19 with Mathematics categories.
Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website.
Time Series
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Author : David R. Brillinger
language : en
Publisher: SIAM
Release Date : 2001-09-01
Time Series written by David R. Brillinger and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-09-01 with Mathematics categories.
This text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals.
Fourier Analysis Of Time Series
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Author : Peter Bloomfield
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-05
Fourier Analysis Of Time Series written by Peter Bloomfield 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 2004-04-05 with Mathematics categories.
A new, revised edition of a yet unrivaled work on frequency domain analysis Long recognized for his unique focus on frequency domain methods for the analysis of time series data as well as for his applied, easy-to-understand approach, Peter Bloomfield brings his well-known 1976 work thoroughly up to date. With a minimum of mathematics and an engaging, highly rewarding style, Bloomfield provides in-depth discussions of harmonic regression, harmonic analysis, complex demodulation, and spectrum analysis. All methods are clearly illustrated using examples of specific data sets, while ample exercises acquaint readers with Fourier analysis and its applications. The Second Edition: * Devotes an entire chapter to complex demodulation * Treats harmonic regression in two separate chapters * Features a more succinct discussion of the fast Fourier transform * Uses S-PLUS commands (replacing FORTRAN) to accommodate programming needs and graphic flexibility * Includes Web addresses for all time series data used in the examples An invaluable reference for statisticians seeking to expand their understanding of frequency domain methods, Fourier Analysis of Time Series, Second Edition also provides easy access to sophisticated statistical tools for scientists and professionals in such areas as atmospheric science, oceanography, climatology, and biology.
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.
Singular Spectrum Analysis For Time Series
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Author : Nina Golyandina
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-19
Singular Spectrum Analysis For Time Series written by Nina Golyandina 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 2013-01-19 with Mathematics categories.
Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA seeks to decompose the original series into a sum of a small number of interpretable components such as trend, oscillatory components and noise. It is based on the singular value decomposition of a specific matrix constructed upon the time series. Neither a parametric model nor stationarity are assumed for the time series. This makes SSA a model-free method and hence enables SSA to have a very wide range of applicability. The present book is devoted to the methodology of SSA and shows how to use SSA both safely and with maximum effect. Potential readers of the book include: professional statisticians and econometricians, specialists in any discipline in which problems of time series analysis and forecasting occur, specialists in signal processing and those needed to extract signals from noisy data, and students taking courses on applied time series analysis.
Spectral Analysis Of Economic Time Series Psme 1
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Author : Clive William John Granger
language : en
Publisher: Princeton University Press
Release Date : 2015-12-08
Spectral Analysis Of Economic Time Series Psme 1 written by Clive William John Granger and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-08 with Business & Economics categories.
The important data of economics are in the form of time series; therefore, the statistical methods used will have to be those designed for time series data. New methods for analyzing series containing no trends have been developed by communication engineering, and much recent research has been devoted to adapting and extending these methods so that they will be suitable for use with economic series. This book presents the important results of this research and further advances the application of the recently developed Theory of Spectra to economics. In particular, Professor Hatanaka demonstrates the new technique in treating two problems-business cycle indicators, and the acceleration principle existing in department store data. Originally published in 1964. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Spectral Analysis For Univariate Time Series
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Author : Donald B. Percival
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-31
Spectral Analysis For Univariate Time Series written by Donald B. Percival and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Mathematics categories.
Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website.