Time Series Analysis and Applications to Geophysical Systems

1. Front Matter

   Pages i-xii

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2. Interpretation of Seismic Signals

   1. Nonparametric Deconvolution of Seismic Depth Phases

      • Robert H. Shumway, Jessie L. Bonner, Delaine T. Reiter

      Pages 1-10

   2. State Space Approach to Signal Extraction Problems in Seismology

      • Genshiro Kitagawa, Tetsuo Takanami, Norio Matsumoto

      Pages 11-39

   3. Improved Signal Transmission through Randomization

      • Enders A. Robinson

      Pages 41-51

   4. Online Analysis of Seismic Signals

      • Hernando Ombao, Jungeon Heo, David Stoffer

      Pages 53-71

3. Temperature Data

   1. Nonstationary Time Series Analysis of Monthly Global Temperature Anomalies

      • T. Subba Rao, E. P. Tsolaki

      Pages 73-103

   2. A Test for Detecting Changes in Mean

      • Wei Biao Wu

      Pages 105-121

   3. Spatio-temporal Modelling of Temperature Time Series: A Comparative Study

      • T. Subba Rao, Ana Monica Costa Antunes

      Pages 123-150

   4. Modeling North Pacific Climate Time Series

      • Donald B. Percival, James E. Overland, Harold O. Mofjeld

      Pages 151-167

4. Assortment of Important Time Series Problems and Applications

   1. Skew-elliptical Time Series with Application to Flooding Risk

      • Marc G. Genton, Keith R. Thompson

      Pages 169-185

   2. Hidden Periodicities Analysis and Its Application in Geophysics

      • Zhongjie Xie

      Pages 187-194

   3. The Innovation Approach to the Identification of Nonlinear Causal Models in Time Series Analysis

      • T. Ozaki, J. C. Jimenez, H. Peng, V. H. Ozaki

      Pages 195-226

   4. Non-Gaussian Time Series Models

      • Murray Rosenblatt

      Pages 227-237

   5. Modeling Continuous Time Series Driven by Fractional Gaussian Noise

      • Winston C. Chow, Edward J. Wegman

      Pages 239-255

5. Back Matter

   Pages 257-260

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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.

• STATISTICA
• geophysics
• modeling
• nonlinear system
• statistics

• Department of Statistics, University of California, Berkeley, Berkeley, USA

  David R. Brillinger

• Department of Earth and Environmental Engineering Henry Krumb School of Mines, Columbia University, New York, USA

  Enders Anthony Robinson

• Department of Statistics, University of California, Los Angeles, Los Angeles, USA

  Frederic Paik Schoenberg

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