Time Series in the Time Domain

Edited by

  • E.J. Hannan
  • P.R. Krishnaiah
  • M.M. Rao

In this volume prominent workers in the field discuss various time series methods in the time domain. The topics included are autoregressive-moving average models, control, estimation, identification, model selection, non-linear time series, non-stationary time series, prediction, robustness, sampling designs, signal attenuation, and speech recognition. This volume complements Handbook of Statistics 3: Time Series in the Frequency Domain.
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Book information

  • Published: August 1985
  • Imprint: ELSEVIER
  • ISBN: 978-0-444-87629-4

Table of Contents

Nonstationary Autoregressive Time Series (W.A. Fuller). Non-Linear Time Series Models and Dynamical Systems (T. Ozaki). Autoregressive Moving Average Models, Intervention Problems and Outlier Detection in Time Series (G.C. Tiao). Robustness in Time Series and Estimating ARMA Models (R.D. Martin, V.J. Yohai). Time Series Analysis with Unequally Spaced Data (R.H. Jones). Various Model Selection Techniques in Time Series Analysis (R. Shibata). Estimation of Parameters in Dynamical Systems (L. Ljung). Recursive Identification, Estimation and Control (P. Young). General Structure and Parametrization of ARMA and State-Space Systems and its Relation to Statistical Problems (M.D. Deistler). Harmonizable, Cramér, and Karhunen Classes of Processes (M.M. Rao). On Non-Stationary Time Series (C.S.K. Bhagavan). Harmonizable Filtering and Sampling to Time Series (D.K. Chang). Sampling Designs for Time Series (S. Cambanis). Measuring Attenuation (M.A. Cameron, P.J. Thomson). Speech Recognition Using LPC Distance Measures (P.J. Thomson, P. De Souza). Varying Coefficient Regression (D.F. Nicholls, A.R. Pagan). Small Samples and Large Equation Systems (H. Theil, D.G. Fiebig). Index.