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A Sampling Study of Minimum Absolute Deviations Estimators

Author

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  • V. G. Ashar

    (North Carolina State College)

  • T. D. Wallace

    (North Carolina State College)

Abstract

Small sample properties of minimum absolute deviations estimators were studied via a simulation model. A four-parameter model of full rank was proposed and 50 random samples were drawn consistent with this model. Results indicated that, for this experiment, m a d estimators were about 20 per cent efficient compared to minimum variance estimators, using Aitken's concept of generalized efficiency. No significant biases were found in the experiment.

Suggested Citation

  • V. G. Ashar & T. D. Wallace, 1963. "A Sampling Study of Minimum Absolute Deviations Estimators," Operations Research, INFORMS, vol. 11(5), pages 747-758, October.
    • Handle: RePEc:inm:oropre:v:11:y:1963:i:5:p:747-758
    DOI: 10.1287/opre.11.5.747
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    Cited by:

    1. Yanagida, John F. & Book, Don N., 1984. "Application of the Least Absolute Value Technique as a Data Filter for Detecting Structural Change in the Demand for Meat," Journal of the Northeastern Agricultural Economics Council, Northeastern Agricultural and Resource Economics Association, vol. 13(1), pages 1-5, April.
    2. Disney, W. Terry & Duffy, Patricia A. & Hardy, William E., Jr., 1988. "A Markov Chain Analysis Of Pork Farm Size Distributions In The South," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 20(2), pages 1-8, December.
    3. Miller, Douglas J., 1994. "Entropy Methods For Recovering Information From Economic Models," 1994 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses Risk, Technical Committee Meeting, March 24-26, 1994, Gulf Shores State Park, Alabama 271680, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    4. Houck, James P. & Hunt, R.D., 1968. "Using Absolute Deviations To Compute Lines Of Best Fit," Staff Papers 13732, University of Minnesota, Department of Applied Economics.

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