Least absolute deviation estimation of stationary time series models

W. T M Dunsmuir; B. A. Murtagh

doi:10.1016/0377-2217(93)90068-X

Least absolute deviation estimation of stationary time series models

W. T M Dunsmuir^*, B. A. Murtagh

^*Corresponding author for this work

Macquarie Graduate School of Management

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	272-277
Number of pages	6
Journal	European Journal of Operational Research
Volume	67
Issue number	2
DOIs	https://doi.org/10.1016/0377-2217(93)90068-X
Publication status	Published - 11 Jun 1993

Keywords

LAD estimation
Moving averages
Non-linear programming

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10.1016/0377-2217(93)90068-X

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title = "Least absolute deviation estimation of stationary time series models",

abstract = "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.",

keywords = "LAD estimation, Moving averages, Non-linear programming",

author = "Dunsmuir, {W. T M} and Murtagh, {B. A.}",

year = "1993",

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AU - Murtagh, B. A.

PY - 1993/6/11

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N2 - 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.

AB - 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.

KW - LAD estimation

KW - Moving averages

KW - Non-linear programming

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U2 - 10.1016/0377-2217(93)90068-X

DO - 10.1016/0377-2217(93)90068-X

M3 - Article

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EP - 277

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

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ER -

Least absolute deviation estimation of stationary time series models

Abstract

Keywords

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