The Spectral Analysis of Time Series
eBook - PDF

The Spectral Analysis of Time Series

Probability and Mathematical Statistics, Vol. 22

  1. 382 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

The Spectral Analysis of Time Series

Probability and Mathematical Statistics, Vol. 22

About this book

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.

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Yes, you can access The Spectral Analysis of Time Series by L. H. Koopmans, Z. W. Birnbaum,E. Lukacs in PDF and/or ePUB format, as well as other popular books in Mathematics & Applied Mathematics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2014
Print ISBN
9780124192508
eBook ISBN
9781483218540
Topic
Mathematics
Subtopic
Applied Mathematics
Index
Mathematics

Table of contents

  1. Front Cover
  2. The Spectral Analysis of Time Series
  3. Copyright Page
  4. Table of Contents
  5. Dedication
  6. Preface
  7. Acknowledgments
  8. Chapter 1. Preliminaries
  9. Chapter 2. Models for Spectral Analysis—The Univariate Case
  10. Chapter 3. Sampling, Aliasing, and Discrete-Time Models
  11. Chapter 4. Linear Filters—General Properties with Applications to Continuous-Time Processes
  12. Chapter 5. Multivariate Spectral Models and Their Applications
  13. Chapter 6. Digital Filters
  14. Chapter 7. Finite Parameter Models, Linear Prediction, and Real-Time Filtering
  15. Chapter 8. The Distribution Theory of Spectral Estimates with Applications to Statistical Inference
  16. Chapter 9. Sampling Properties of Spectral Estimates, Experimental Design, and Spectral Computations
  17. References
  18. Index