Fourier Analysis of Time Series: An Introduction by Peter Bloomfield

From the Publisher

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.

Technometrics

These two new books are both new editions of time series classics that will be welcomed by practitioners.

Short Book Reviews

The first edition stood out as a model...this new edition holds up very successfully while incorporating a quarter century of change.

Technometrics

These two new books are both new editions of time series classics that will be welcomed by practitioners.

Booknews

Updating his 1976 textbook for graduate or undergraduate students who encounter a course on time series methods in statistics while innocently studying such subjects as atmospheric science or biology, and for workers in those fields who stumble across time series data, Bloomfield (statistics, North Carolina State U.-Raleigh) assumes only an introductory course in statistics. All the methods he describes are introduced in the context of specific sets of data, so that the motivation behind a method is evident as it is developed. Fourier analysis and the Fourier transform being a frequent impediment, he spends an entire chapter introducing what really is an elementary form of mathematics just applied over and over. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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