The spectral analysis of time series
By: Lambert H. Koopmans.
Edition: [2nd ed.].
Series: Probability and mathematical statistics ;; v. 22
Publisher: Academic Press
Published: 1995
Place of publication: San Diego
Language: eng
Number of pages: 366
Subjects: Time-series analysis; Spectral theory (Mathematics)
Description: A Volume in the Probability and Mathematical Statistics Series.

To tailor time series models to a particular physical problem and to follow the working of various techniques for processing and analyzing data, one must understand the basic theory of spectral (frequency domain) analysis of time series. This classic book provides an introduction to the techniques and theories of spectral analysis of time series. In a discursive style, and with minimal dependence on mathematics, the book presents the geometric structure of spectral analysis.

This approach makes possible useful, intuitive interpretations of important time series parameters and provides a unified framework for an otherwise scattered collection of seemingly isolated results.

The book's strength lies in its applicability to the needs of readers from many disciplines with varying backgrounds in mathematics. It provides a solid foundation in spectral analysis for fields that include statistics, signal process engineering, economics, geophysics, physics, and geology. Appendices provide details and proofs for those who are advanced in math. Theories are followed by examples and applications over a wide range of topics such as meteorology, seismology, and telecommunications.

Topics covered include Hilbert spaces; univariate models for spectral analysis; multivariate spectral models; sampling, aliasing, and discrete-time models; real-time filtering; digital filters; linear filters; distribution theory; sampling properties of spectral estimates; and linear prediction.
Notes: Includes bibliographical references (p. 354-358) and index.