A Nonlinear Time Series Workshop: A Toolkit for Detecting and Identifying Nonlinear Serial Dependence / Edition 1

by Douglas M. Patterson, Richard A. Ashley

Overview

The complex dynamic behavior exhibited by many nonlinear systems - chaos, episodic volatility bursts, shastic regimes switching - has attracted a good deal of attention in recent years. A Nonlinear Time Series Workshop provides the reader with both the statistical background and the software tools necessary for detecting nonlinear behavior in time series data. The most useful existing detection techniques are described, including Engle's LaGrange Multiplier test for conditional hetero-skedasticity and tests based on the correlation dimension and on the estimated bispectrum. These techniques are illustrated using actual data from fields such as economics, finance, engineering, and geophysics.

Product Details

ISBN-13:	9780792386742
Publisher:	Springer US
Publication date:	10/31/1999
Series:	Dynamic Modeling and Econometrics in Economics and Finance , #2
Edition description:	2000
Pages:	201
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

1. Nonlinearity in Shastic Processes: What it Is and Why it Matters.- 2. Detecting Nonlinear Serial Dependence.- 3. How to Run the Toolkit Program on a PC.- 4. Artificially Generated Data: Size Considerations.- 5. Artificially Generated Data: Power And Model Specification Considerations.- 6. Analysis of Sk Market Returns.- 7. Glint Tracking Errors in Radar.- 8. Seismic Data.- 9. Analysis of U.S. Real GNP.- 10. Dynamic Structure of Macroeconomic Technology Shocks.- 11. Climatological Data.