The Role of Linear Recursive Estimators in Time Series Forecasting

Article Abstract:

This paper presents a descriptive synthesis of a number of a linear recursive estimator (LRE) procedures for time series forecasting, i.e., procedures which involve parameter updates proportional to the period forecast error. It is stressed that both constant and variable parameter procedures exist among LRE's. General requirements for stability of parameter estimates are given, as are general forms for parameter estimate covariance matrices that appear in forecast variance determinations. Procedures explicitly considered are the Kalman filter, dynamic autoregression, the Carbone-Longini adaptive estimation procedure, generalized least squares, Widrow's least mean square, and the Makridakis-Wheelwright generalized adaptive filtering. (Reprinted by Permission of Publisher.)

Management science, Parameter estimation, Kalman filtering, Estimation, Parameters, Approximation, Filtering, Least Squares Approximation, Recursion, Linear Algebra

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The role of linear recursive estimators in time series forecasting

Article Abstract:

Time series forecasts that use linear recursive estimation processes are analyzed, and new procedures for such forecasting techniques are developed. Time series forecasts update parameters in given mathematical models, based upon an analysis of the errors detected in the most recent period of forecast. The parameter updating processes examined are applicable to both constant and variable procedural analyses. Among the procedures analyzed are: the Kalman filter, dynamic autoregression, the Carbone-Longini adaptive estimator process, generalized least squares analyses, Widrow's least mean square procedure, and Makridakis-Wheelwright adaptive generalized filtering processes.

Research, Models, Linear programming, Case studies, Economic forecasting, Business forecasting, Time-series analysis, Time series analysis, Recursive functions

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A Diverting Structures Effects on a River Flow Time Series

Article Abstract:

An approach to the measurement of the time series effects of public policy decisions is called intervention analysis. The measurement of the impact of a newly constructed dam on the flow rate of a river is studied. This problem is a specific case of a larger set of problems centering on public policy decisions concerning diverting structures on or near bodies of water. Graphs of weekly rainfall rates are included. Numerical results are presented in tables and graphs.

Statistics (Data), Modeling, Data modeling software, Statistics, Time Series, Water Management

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