9780387978963-0387978968-Time Series Analysis and Applications to Geophysical Systems: Part I (The IMA Volumes in Mathematics and its Applications, 45)

Time Series Analysis and Applications to Geophysical Systems: Part I (The IMA Volumes in Mathematics and its Applications, 45)

ISBN-13: 9780387978963
ISBN-10: 0387978968
Author: Murray Rosenblatt, John Geweke, Murad S. Taqqu, Emanuel Parzen, David Brillinger, Peter Caines
Publication date: 1992
Publisher: Springer
Format: Hardcover 407 pages
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ISBN-13: 9780387978963
ISBN-10: 0387978968
Author: Murray Rosenblatt, John Geweke, Murad S. Taqqu, Emanuel Parzen, David Brillinger, Peter Caines
Publication date: 1992
Publisher: Springer
Format: Hardcover 407 pages

Summary

Time Series Analysis and Applications to Geophysical Systems: Part I (The IMA Volumes in Mathematics and its Applications, 45) (ISBN-13: 9780387978963 and ISBN-10: 0387978968), written by authors Murray Rosenblatt, John Geweke, Murad S. Taqqu, Emanuel Parzen, David Brillinger, Peter Caines, was published by Springer in 1992. With an overall rating of 3.5 stars, it's a notable title among other books. You can easily purchase or rent Time Series Analysis and Applications to Geophysical Systems: Part I (The IMA Volumes in Mathematics and its Applications, 45) (Hardcover) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Part of a two volume set based on a recent IMA program of the same name. The goal of the program and these books is to develop a community of statistical and other scientists kept up-to-date on developments in this quickly evolving and interdisciplinary field. Consequently, these books present recent material by distinguished researchers. Topics discussed in Part I include nonlinear and non- Gaussian models and processes (higher order moments and spectra, nonlinear systems, applications in astronomy, geophysics, engineering, and simulation) and the interaction of time series analysis and statistics (information model identification, categorical valued time series, nonparametric and semiparametric methods). Self-similar processes and long-range dependence (time series with long memory, fractals, 1/f noise, stable noise) and time series research common to engineers and economists (modeling of multivariate and possibly non-stationary time series, state space and adaptive methods) are discussed in Part II.

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