Full Read and Download Reference eBook
Spectral Analysis And Time Series Two Volume Set Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Spectral Analysis And Time Series Two Volume Set book. This book definitely worth reading, it is an incredibly well-written.
Author : M. B. Priestley
Publisher : Academic Press
Page : 972 pages
File Size : 21,87 MB
Release : 1982
Category : Mathematics
ISBN :
Enth.: Univariate series ; Multivariate series, prediction and control.
Author : L. H. Koopmans
Publisher : Academic Press
Page : 383 pages
File Size : 44,77 MB
Release : 2014-05-12
Category : Mathematics
ISBN : 1483218546
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.
Author : Lambert Herman Koopmans
Publisher :
Page : 390 pages
File Size : 29,16 MB
Release : 1974
Category : Mathematics
ISBN :
The Spectral Analysis of Time Series ...
Author : Rebecca M. Warner
Publisher : Guilford Press
Page : 244 pages
File Size : 33,97 MB
Release : 1998-05-22
Category : Social Science
ISBN : 9781572303386
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.
Author : M. B. Priestley
Publisher : Academic Press
Page : 890 pages
File Size : 32,7 MB
Release : 1983-02-11
Category : Mathematics
ISBN : 9780125649223
A principal feature of this book is the substantial care and attention devoted to explaining the basic ideas of the subject. Whenever a new theoretical concept is introduced it is carefully explained by reference to practical examples drawn mainly from the physical sciences. Subjects covered include: spectral analysis which is closely intertwined with the "time domain" approach, elementary notions of Hilbert Space Theory, basic probability theory, and practical analysis of time series data. The inclusion of material on "kalman filtering", state-space filtering", "non-linear models" and continuous time" models completes the impressive list of unique and detailed features which will give this book a prominent position among related literature. The first section-Volume 1-deals with single (univariate) series, while the second-Volume 2-treats the analysis of several (multivariate) series and the problems of prediction, forecasting and control.
Author : Donald B. Percival
Publisher : Cambridge University Press
Page : 718 pages
File Size : 50,88 MB
Release : 2020-03-19
Category : Mathematics
ISBN : 1108776175
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.
Author : G. Larry Bretthorst
Publisher : Springer Science & Business Media
Page : 210 pages
File Size : 20,94 MB
Release : 2013-03-09
Category : Mathematics
ISBN : 146849399X
This work is essentially an extensive revision of my Ph.D. dissertation, [1J. It 1S primarily a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis; consequently, we have included a great deal of introductory and tutorial material. Any person with the equivalent of the mathematics background required for the graduate level study of physics should be able to follow the material contained in this book, though not without eIfort. From the time the dissertation was written until now (approximately one year) our understanding of the parameter estimation problem has changed extensively. We have tried to incorporate what we have learned into this book. I am indebted to a number of people who have aided me in preparing this docu ment: Dr. C. Ray Smith, Steve Finney, Juana Sunchez, Matthew Self, and Dr. Pat Gibbons who acted as readers and editors. In addition, I must extend my deepest thanks to Dr. Joseph Ackerman for his support during the time this manuscript was being prepared.
Author : S. Lawrence Marple, Jr.
Publisher : Courier Dover Publications
Page : 435 pages
File Size : 26,57 MB
Release : 2019-03-20
Category : Technology & Engineering
ISBN : 0486838862
Designed to offer a broad perspective on spectral estimations techniques and their implementation, this text provides theoretical background and review material in linear systems, Fourier transforms, matrix algebra, random processes, and statistics. 1987 edition.
Author : Nina Golyandina
Publisher : Springer Science & Business Media
Page : 126 pages
File Size : 34,23 MB
Release : 2013-01-19
Category : Mathematics
ISBN : 3642349137
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.
Author : M. B. Priestley
Publisher : Academic Press
Page : 0 pages
File Size : 12,79 MB
Release : 1983-01-28
Category : Mathematics
ISBN : 9780125649223
A principal feature of this book is the substantial care and attention devoted to explaining the basic ideas of the subject. Whenever a new theoretical concept is introduced it is carefully explained by reference to practical examples drawn mainly from the physical sciences. Subjects covered include: spectral analysis which is closely intertwined with the "time domain" approach, elementary notions of Hilbert Space Theory, basic probability theory, and practical analysis of time series data. The inclusion of material on "kalman filtering", state-space filtering", "non-linear models" and continuous time" models completes the impressive list of unique and detailed features which will give this book a prominent position among related literature. The first section-Volume 1-deals with single (univariate) series, while the second-Volume 2-treats the analysis of several (multivariate) series and the problems of prediction, forecasting and control.