Time Series With Mixed Spectra
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| Author | : Ta-Hsin Li |
| Publisher | : CRC Press |
| Total Pages | : 648 |
| Release | : 2016-04-19 |
| Genre | : Mathematics |
| ISBN | : 1420010069 |
Time series with mixed spectra are characterized by hidden periodic components buried in random noise. Despite strong interest in the statistical and signal processing communities, no book offers a comprehensive and up-to-date treatment of the subject. Filling this void, Time Series with Mixed Spectra focuses on the methods and theory for the stati
| Author | : L. H. Koopmans |
| Publisher | : Academic Press |
| Total Pages | : 383 |
| Release | : 2014-05-12 |
| Genre | : 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 | : Donald B. Percival |
| Publisher | : Cambridge University Press |
| Total Pages | : 718 |
| Release | : 2020-03-19 |
| Genre | : 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 | : Lucien Marie Le Cam |
| Publisher | : Univ of California Press |
| Total Pages | : 690 |
| Release | : 1967 |
| Genre | : Mathematical statistics |
| ISBN | : |
| Author | : A.R. Rao |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 392 |
| Release | : 2012-12-06 |
| Genre | : Science |
| ISBN | : 9401001170 |
Conventionally, time series have been studied either in the time domain or the frequency domain. The representation of a signal in the time domain is localized in time, i.e . the value of the signal at each instant in time is well defined . However, the time representation of a signal is poorly localized in frequency , i.e. little information about the frequency content of the signal at a certain frequency can be known by looking at the signal in the time domain . On the other hand, the representation of a signal in the frequency domain is well localized in frequency, but is poorly localized in time, and as a consequence it is impossible to tell when certain events occurred in time. In studying stationary or conditionally stationary processes with mixed spectra , the separate use of time domain and frequency domain analyses is sufficient to reveal the structure of the process . Results discussed in the previous chapters suggest that the time series analyzed in this book are conditionally stationary processes with mixed spectra. Additionally, there is some indication of nonstationarity, especially in longer time series.
| Author | : Hans Gilgen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 734 |
| Release | : 2006-01-16 |
| Genre | : Science |
| ISBN | : 3540309683 |
This is a detailed introduction to the statistical analysis of geophysical time series, using numerous examples and exercises to build proficiency. The exercises lead the reader to explore the meaning of concepts such as the estimation of the linear time series (AMRA) models or spectra. The book also serves as a guide to using the open-source "R" program for statistical analysis of time series.
| Author | : Gilles Dufrénot |
| Publisher | : Springer Nature |
| Total Pages | : 387 |
| Release | : 2020-11-21 |
| Genre | : Business & Economics |
| ISBN | : 3030542521 |
The book provides a comprehensive overview of the latest econometric methods for studying the dynamics of macroeconomic and financial time series. It examines alternative methodological approaches and concepts, including quantile spectra and co-spectra, and explores topics such as non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization. Furthermore, it demonstrates the application of recent techniques in various fields: in the frequency domain, in the analysis of persistent dynamics, in the estimation of state space models and new classes of volatility models. The book is divided into two parts: The first part applies econometrics to the field of macroeconomics, discussing trend/cycle decomposition, growth analysis, monetary policy and international trade. The second part applies econometrics to a wide range of topics in financial economics, including price dynamics in equity, commodity and foreign exchange markets and portfolio analysis. The book is essential reading for scholars, students, and practitioners in government and financial institutions interested in applying recent econometric time series methods to financial and economic data.
| Author | : D. M. Titterington |
| Publisher | : |
| Total Pages | : 404 |
| Release | : 2001 |
| Genre | : Mathematics |
| ISBN | : 9780198509936 |
The year 2001 marks the centenary of Biometrika, one of the world's leading academic journals in statistical theory and methodology. In celebration of this, the book brings together two sets of papers from the journal. The first comprises seven specially commissioned articles (authors: D.R. Cox, A.C. Davison, Anthony C. Atkinson and R.A. Bailey, David Oakes, Peter Hall, T.M.F. Smith, and Howell Tong). These articles review the history of the journal and the most important contributions made by appearing in the journal in a number of important areas of statitisical activity, including general theory and methodology, surveys and time sets. In the process the papers describe the general development of statistical science during the twentieth century. The second group of ten papers are a selection of particularly seminal articles form the journal's first hundred years. The book opens with an introduction by the editors Professor D.M. Titterington and Sir David Cox.
| Author | : Manfred Mudelsee |
| Publisher | : Springer |
| Total Pages | : 477 |
| Release | : 2014-06-27 |
| Genre | : Science |
| ISBN | : 3319044508 |
Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. “....comprehensive mathematical and statistical summary of time-series analysis techniques geared towards climate applications...accessible to readers with knowledge of college-level calculus and statistics.” (Computers and Geosciences) “A key part of the book that separates it from other time series works is the explicit discussion of time uncertainty...a very useful text for those wishing to understand how to analyse climate time series.” (Journal of Time Series Analysis) “...outstanding. One of the best books on advanced practical time series analysis I have seen.” (David J. Hand, Past-President Royal Statistical Society)
| Author | : Jyotiprasad Medhi |
| Publisher | : New Age International |
| Total Pages | : 664 |
| Release | : 1994 |
| Genre | : Procesos estocásticos |
| ISBN | : 9788122405491 |
Aims At The Level Between That Of Elementary Probability Texts And Advanced Works On Stochastic Processes. The Pre-Requisites Are A Course On Elementary Probability Theory And Statistics, And A Course On Advanced Calculus. The Theoretical Results Developed Have Been Followed By A Large Number Of Illustrative Examples. These Have Been Supplemented By Numerous Exercises, Answers To Most Of Which Are Also Given. It Will Suit As A Text For Advanced Undergraduate, Postgraduate And Research Level Course In Applied Mathematics, Statistics, Operations Research, Computer Science, Different Branches Of Engineering, Telecommunications, Business And Management, Economics, Life Sciences And So On. A Review Of The Book In American Mathematical Monthly (December 82) Gives This Book Special Positive Emphasis As A Textbook As Follows: 'Of The Dozen Or More Texts Published In The Last Five Years Aimed At The Students With A Background Of A First Course In Probability And Statistics But Not Yet To Measure Theory, This Is The Clear Choice. An Extremely Well Organized, Lucidly Written Text With Numerous Problems, Examples And Reference T* (With T* Where T Denotes Textbook And * Denotes Special Positive Emphasis). The Current Enlarged And Revised Edition, While Retaining The Structure And Adhering To The Objective As Well As Philosophy Of The Earlier Edition, Removes The Deficiencies, Updates The Material And The References And Aims At A Border Perspective With Substantial Additions And Wider Coverage.
