Applied Time Series Analysis II - 1st Edition - ISBN: 9780122564208, 9781483263908

Applied Time Series Analysis II

1st Edition

Proceedings of the Second Applied Time Series Symposium Held in Tulsa, Oklahoma, March 3-5, 1980

Editors: David F. Findley
eBook ISBN: 9781483263908
Imprint: Academic Press
Published Date: 28th November 1981
Page Count: 810
Sales tax will be calculated at check-out Price includes VAT/GST
15% off
15% off
15% off
Price includes VAT/GST
× DRM-Free

Easy - Download and start reading immediately. There’s no activation process to access eBooks; all eBooks are fully searchable, and enabled for copying, pasting, and printing.

Flexible - Read on multiple operating systems and devices. Easily read eBooks on smart phones, computers, or any eBook readers, including Kindle.

Open - Buy once, receive and download all available eBook formats, including PDF, EPUB, and Mobi (for Kindle).

Institutional Access

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.


Applied Time Series Analysis II contains the proceedings of the Second Applied Time Series Symposium Held in Tulsa, Oklahoma, on March 3-5, 1980. The symposium provided a forum for discussing significant advances in time series analysis and signal processing. Effective alternatives to the familiar least-square and maximum likelihood procedures are described, along with maximum likelihood procedures for modeling irregularly sampled series and for classifying non-stationary series.

Comprised of 22 chapters, this volume begins with an introduction to the multidimensional filtering theory and presents specific case histories related to the multidimensional recursive filter stability problem; the least squares inverse problem; realization of filters; and spectral estimation. The unique properties of the three-dimensional wave equation are also considered. Subsequent chapters focus on high-resolution spectral estimators; time series analysis of geophysical inverse scattering problems; minimum entropy deconvolution; and fitting of a continuous time autoregression to discrete data.

This monograph will appeal to students and practitioners in the fields of mathematics and statistics, electrical and electronics engineering, and information and computer sciences.

Table of Contents



Introduction to the Papers

The Step from One to Higher Dimensional Signal Processing - Case Histories

High Resolution 2-Dimensional Power Spectral Estimation

Time Series Analysis of Geophysical Inverse Scattering Problems

On the Use of the Fourier Transforms to Image Seismic Reflection Data

Estimating the Earth's Impedence Function When There Is Noise in the Electric and Magnetic Signals

Nearest Neighbor Rule Classification of Stationary and Nonstationary Time Series

Time Domain Considerations in Optimal Estimation for Bandlimited Signals

Lattice Methods in Spectral Estimation

Geometrical and Lattice Versions of Levinson's General Algorithm

Order Selection for Lowpass IIR Filters

Application of S-Arrays to Seasonal Data

Time Series Model Identification and Prediction Variance Horizon

Recursive Estimation and Adaptive Forecasting in ARIMA Models with Time Varying Coefficients

A Time Series Case Study from Biology: Some Interplay Between Theory and Practice


Phase-Sensitive Deconvolution to Model Random Processes, with Special Reference to Astronomical Data

On Minimum Entropy Deconvolution

Estimation for Stationary Time Series When Data Are Irregularly Spaced or Missing

Fitting a Continous Time Autoregression to Discrete Data

Robust Methods for Time Series

Robust Forecasting



No. of pages:
© Academic Press 1981
Academic Press
eBook ISBN:

About the Editor

David F. Findley

Ratings and Reviews