New Directions in Time Series Analysis

1. Front Matter

   Pages i-xviii

   PDF

2. Recent Developments in Location Estimation and Regression for Long-Memory Processes

   • Jan Beran

   Pages 1-9

3. Phase-Transition in Statistical Physical Models with Discrete and Continuous Symmetries

   • P. M. Bleher, P. Major

   Pages 11-20

4. Identification of Linear Systems from Noisy Data

   • M. Deistler, W. Scherrer

   Pages 21-42

5. Unit Roots in U.S. Macroeconomic Time Series: A Survey of Classical and Bayesian Perspectives

   • David N. Dejong, Charles H. Whiteman

   Pages 43-69

6. A Nonparametric Approach to Nonlinear Time Series Analysis: Estimation and Simulation

   • A. Ronald Gallant, George Tauchen

   Pages 71-92

7. Asymptotics of Predictive Stochastic Complexity

   • László Gerencsér, Jorma Rissanen

   Pages 93-112

8. Smoothness Priors

   • Will Gersch

   Pages 113-146

9. An Extension of Quadrature-Based Methods for Solving Euler Conditions

   • Eric Ghysels, Alastair Hall

   Pages 147-151

10. Long Memory Shot Noises and Limit Theorems with Application to Burgers’ Equation

    • L. Giraitis, S. A. Molchanov, D. Surgailis

    Pages 153-176

11. On Approximate Modeling of Linear Gaussian Processes

    • Andrea Gombani, Claudia Polini

    Pages 177-193

12. On the Identification and Prediction of Nonlinear Models

    • D. Guegan

    Pages 195-210

13. Identification of Stochastic Time-Varying Parameters

    • L. Guo, H. F. Chen, J. F. Zhang

    Pages 211-223

14. Convergence of Åström-Wittenmark’s Self-Tuning Regulator and Related Topics

    • Lei Guo, Han-Fu Chen

    Pages 225-238

15. On the Closure of Several Sets of ARMA and Linear State Space Models with a Given Structure

    • B. Hanzon

    Pages 239-253

16. Weak Convergence to Self-Affine Processes in Dynamical Systems

    • Michael Lacey

    Pages 255-262

17. Recursive Estimation in Armax Models

    • Tze Leung Lai

    Pages 263-288

18. On Adaptive Stabilization and Ergodic Behaviour of Systems with Jump-Markov Parameters Via Nonlinear Filtering

    • Karim Nassiri-Toussi, Peter E. Caines

    Pages 289-314

19. The Convergence of output Error Recursions in Infinite Order Moving Average Noise

    • Wei Ren, P. R. Kumar

    Pages 315-324

20. Linear Models with Long-Range Dependence and with Finite or Infinite Variance

    • Gennady Samorodnitsky, Murad S. Taqqu

    Pages 325-340

This IMA Volume in Mathematics and its Applications NEW DIRECTIONS IN TIME SERIES ANALYSIS, PART II is based on the proceedings of the IMA summer program "New Directions in Time Series Analysis. " We are grateful to David Brillinger, Peter Caines, John Geweke, Emanuel Parzen, Murray Rosenblatt, and Murad Taqqu for organizing the program and we hope that the remarkable excitement and enthusiasm of the participants in this interdisciplinary effort are communicated to the reader. A vner Friedman Willard Miller, Jr. PREFACE Time Series Analysis is truly an interdisciplinary field because development of its theory and methods requires interaction between the diverse disciplines in which it is applied. To harness its great potential, strong interaction must be encouraged among the diverse community of statisticians and other scientists whose research involves the analysis of time series data. This was the goal of the IMA Workshop on "New Directions in Time Series Analysis. " The workshop was held July 2-July 27, 1990 and was organized by a committee consisting of Emanuel Parzen (chair), David Brillinger, Murray Rosenblatt, Murad S. Taqqu, John Geweke, and Peter Caines. Constant guidance and encouragement was provided by Avner Friedman, Director of the IMA, and his very helpful and efficient staff. The workshops were organized by weeks. It may be of interest to record the themes that were announced in the IMA newsletter describing the workshop: l.

• ACE
• Smooth function
• Volume
• boundary element method
• constant
• convergence
• development
• dynamical systems
• field
• filtering
• interaction
• mathematics
• themes
• time
• time series

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

  David Brillinger

• Department of Electrical Engineering, McGill University, Montreal, Canada

  Peter Caines

• Department of Economics, University of Minnesota, Minneapolis, USA

  John Geweke

• Department of Statistics, Texas A&M University, College Station, USA

  Emanuel Parzen

• Mathematics Department, University of California, San Diego, La Jolla, USA

  Murray Rosenblatt

• Department of Mathematics, Boston University, Boston, USA

  Murad S. Taqqu

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