Least absolute deviation estimation of stationary time series models

Least absolute deviation estimation of stationary time series models

This paper is concerned with practical aspects of least absolute deviation (LAD) estimation of Box-Jenkins models for single time series. Formulation of the LAD method as a non-linear programming problem is described. The method is applied to a multiplicative seasonal moving average model for monthl...

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Veröffentlicht in:European journal of operational research 1993-06, Vol.67 (2), p.272-277
Hauptverfasser: Dunsmuir, W.T.M., Murtagh, B.A.
Format: Artikel
Sprache:eng
Schlagworte:
Applied sciences
Estimating techniques
Exact sciences and technology
LAD estimation
Linear programming
Mathematical models
Mathematical programming
Moving averages
Non-linear programming
Nonlinear programming
Operational research and scientific management
Operational research. Management science
Statistical analysis
Time series
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Zusammenfassung:This paper is concerned with practical aspects of least absolute deviation (LAD) estimation of Box-Jenkins models for single time series. Formulation of the LAD method as a non-linear programming problem is described. The method is applied to a multiplicative seasonal moving average model for monthly rice sales data and to US airline passenger data.
ISSN:0377-2217
1872-6860
DOI:10.1016/0377-2217(93)90068-X