Time series in the time domain
Author(s)
Bibliographic Information
Time series in the time domain
（Handbook of statistics, v. 5）
North-Holland , Sole distributors for the U.S.A. and Canada, Elsevier Science Pub. Co., 1985
Available at 163 libraries
Note
Includes bibliographies and index
Description and Table of Contents
Description
In this volume prominent workers in the field discuss various time series methods in the time domain, complementing Volume 3. 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.
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, Cramer, 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.
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