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Fourier Analysis of Time Series: An Introduction (Wiley Series in Probability and Statistics) [Hardcover]

Peter Bloomfield (Author)
5.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

February 4, 2000 0471889482 978-0471889489 2
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.


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Editorial Reviews

Review

"These two new books are both new editions of time series classics that will be welcomed by practitioners." (Technometrics, Vol. 42, No. 4, May 2001)

"The first edition stood out as a model...this new edition holds up very successfully while incorporating a quarter century of change" (Short Book Reviews, December 2000)

"this is a very accessible book" (The Statistician, Vol.50, No.4, 2001)

From the Back Cover

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.

Product Details

  • Hardcover: 288 pages
  • Publisher: Wiley-Interscience; 2 edition (February 4, 2000)
  • Language: English
  • ISBN-10: 0471889482
  • ISBN-13: 978-0471889489
  • Product Dimensions: 9.7 x 6.2 x 0.8 inches
  • Shipping Weight: 1.3 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #666,916 in Books (See Top 100 in Books)

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29 of 29 people found the following review helpful:
5.0 out of 5 stars excellent treatment of frequency domain time series methods, January 23, 2008
This review is from: Fourier Analysis of Time Series: An Introduction (Wiley Series in Probability and Statistics) (Hardcover)
As a time series analyst who studied time series in graduate school when the first edition of Bloomfield's book came out, I really appreciated it. The frequency approach to time series is not natural because we tend to look at the series to see how it changes (fluctuates) over time. This makes the time domain approach very natural. It is only when one sees periodicity in the series and can relate the series to a summation of sine and cosine waves that the frequency domain ideas get appreciated.

Bloomfield introduces Fourier series in a gentle way, making it clear. Concepts are introduced as needed to deal with specific aspects of real time series data.

I particularly liked his treatment of complex demodulation, which could be a very difficult concept to grasp if not presented carefully. But Bloomfield explains it well and provides another way to look at the famous Wolfer sunspot data using an approach based on complex demodulation (assuming a slowly changing period for the series).

The second edition is now out with additional topics and corrections. I have only read the first edition. So my comments only pertain to that edition. This is the best introductory text to frequency domain time series analysis that I have ever read.
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Inside This Book (learn more)
First Sentence:
The simplest use of sinusoids in data analysis is to describe and isolate the periodic part of a series, when the periods are known. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
variable star data, estimated squared coherency, sunspot series, ozone series, periodogram ordinates, annual sunspot numbers, complex demodulation, cross periodogram, lag weights, spectrum estimates, periodogram analysis, sunspot data, spectral distribution function, power transfer function, white noise series, spatial series, estimated phase, spectral density function, spectral weights, stationary time series, spectral window, cross spectrum
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