Santa Fe Time Series Competition book out

Fri Oct 22 03:37:55 EDT 1993

Announcing book on the results of the Santa Fe Time Series Competition:
      ____________________________________________________________________

	Title:  TIME SERIES PREDICTION:
		Forecasting the Future and Understanding the Past.

       Editors: Andreas S. Weigend and Neil A. Gershenfeld

     Publisher: Addison-Wesley, September 1993.
		Paperback ISBN 0-201-62602-0  US$32.25 (672 pages)
		Hardcover ISBN 0-201-62601-2  US$49.50 (672 pages)

		The rest of this message gives some background, 
		ordering information, and the table of contents.
      ____________________________________________________________________

      Most observational disciplines, such as physics, biology, and finance,
try to infer properties of an unfamiliar system from the analysis of a measured
time record of its behavior.  There are many mature techniques associated with
traditional time series analysis.  However, during the last decade, several new
and innovative approaches have emerged (such as neural networks and time-delay
embedding), promising insights not available with these standard methods.

      Unfortunately, the realization of this promise has been difficult.
Adequate benchmarks have been lacking, and much of the literature has been
fragmentary and anecdotal.  

      This volume addresses these shortcomings by presenting the results of a
careful comparison of different methods for time series prediction and
characterization.  This breadth and depth was achieved through the Santa Fe
Time Series Prediction and Analysis Competition, which brought together an
international group of time series experts from a wide variety of fields to
analyze data from the following common data sets:

     -  A physics laboratory experiment (NH3 laser) 
     -  Physiological data from a patient with sleep apnea 
     -  Tick-by-tick currency exchange rate data
     -  A computer-generated series designed specifically for the Competition
     -  Astrophysical data from a variable white dwarf star
     -  J. S. Bach's last (unfinished) fugue from "Die Kunst der Fuge."

In bringing together the results of this unique competition, this volume serves
as a much-needed survey of the latest techniques in time series analysis.

      Andreas Weigend received his Ph.D. from Stanford University
      and was a postdoc at Xerox PARC.  He is Assistant Professor in 
      the Computer Science Department and at the Institute of 
      Cognitive Science at the University of Colorado at Boulder.

      Neil Gershenfeld received his Ph.D. from Cornell University 
      and was a Junior Fellow at Harvard University.  He is Assistant
      Professor at the Media Lab at MIT.
      ____________________________________________________________________

      Order it through your bookstore, or directly from the publisher by
      -  calling the Addison-Wesley Order Department at 1-800-358-4566,
      -  faxing 1-800-333-3328,
      -  emailing <marcuss at world.std.com>, or
      -  writing to Advanced Book Marketing
		    Addison-Wesley Publishing
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     _____________________________________________________________________

     TABLE OF CONTENTS

 xv  Preface
          Andreas S. Weigend and Neil A. Gershenfeld

  1  The Future of Time Series: Learning and Understanding
          Neil A. Gershenfeld and Andreas S. Weigend

Section I.  DESCRIPTION OF THE DATA SETS__________________________________

 73  Lorenz-Like Chaos in NH3-FIR Lasers
          Udo Huebner, Carl-Otto Weiss, Neal Broadus Abraham, and Dingyuan Tang

105  Multi-Channel Physiological Data: Description and Analysis
          David R. Rigney, Ary L. Goldberger, Wendell C. Ocasio, Yuhei Ichimaru, George B. Moody, and Roger G. Mark

131  Foreign Currency Dealing: A Brief Introduction
          Jean Y. Lequarre

139  Whole Earth Telescope Observations of the White Dwarf Star (PG1159-035)
          J. Christopher Clemens

151  Baroque Forecasting: On Completing J.S. Bach's Last Fugue
          Matthew Dirst and Andreas S. Weigend

Section II. TIME SERIES PREDICTION________________________________________

175  Time Series Prediction by Using Delay Coordinate Embedding
          Tim Sauer

195  Time Series Prediction by Using a Connectionist Network with Internal Delay Lines
          Eric A. Wan

219  Simple Architectures on Fast Machines: Practical Issues in Nonlinear Time Series Prediction
          Xiru Zhang and Jim Hutchinson

243  Neural Net Architectures for Temporal Sequence Processing
          Michael C. Mozer

265  Forecasting Probability Densities by Using Hidden Markov Models with Mixed States
          Andrew M. Fraser and Alexis Dimitriadis

283  Time Series Prediction by Using the Method of Analogues
          Eric J. Kostelich and Daniel P. Lathrop

297  Modeling Time Series by Using Multivariate Adaptive Regression Splines (MARS)
          P.A.W. Lewis, B.K. Ray, and J.G. Stevens

319  Visual Fitting and Extrapolation
          George G. Lendaris and Andrew M. Fraser

323  Does a Meeting in Santa Fe Imply Chaos?
          Leonard A. Smith

Section III.  TIME SERIES ANALYSIS AND CHARACTERIZATION___________________

347  Exploring the Continuum Between Deterministic and Stochastic Modeling 
          Martin C. Casdagli and Andreas S. Weigend

367  Estimating Generalized Dimensions and Choosing Time Delays: A Fast Algorithm
          Fernando J. Pineda and John C. Sommerer

387  Identifying and Quantifying Chaos by Using Information-Theoretic Functionals
          Milan Palus

415  A Geometrical Statistic for Detecting Deterministic Dynamics
          Daniel T. Kaplan

429  Detecting Nonlinearity in Data with Long Coherence Times
          James Theiler, Paul S. Linsay, and David M. Rubin

457  Nonlinear Diagnostics and Simple Trading Rules for High-Frequency Foreign Exchange Rates
          Blake LeBaron

475  Noise Reduction by Local Reconstruction of the Dynamics
          Holger Kantz

Section IV.  PRACTICE AND PROMISE_________________________________________

493  Large-Scale Linear Methods for Interpolation, Realization, and Reconstruction of Noisy, Irregularly Sampled Data
          William H. Press and George B. Rybicki

513  Complex Dynamics in Physiology and Medicine
          Leon Glass and Daniel T. Kaplan

529  Forecasting in Economics
          Clive W.J. Granger

539  Finite-Dimensional Spatial Disorder: Description and Analysis
          V.S. Afraimovich, M.I. Rabinovich, and A.L. Zheleznyak

557  Spatio-Temporal Patterns: Observations and Analysis
          Harry L. Swinney

569  Appendix:  Accessing the Server

571  Bibliography (800 references)

631  Index