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An Evaluation of Percentile and Maximum Likelihood Estimators of Weibull Parameters

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Two methods of estimating the three-parameter Weibull distribution were evaluated by computer simulation and field data comparison. Maximum likelihood estimators (MLB) with bias correction were calculated with the computer routine FITTER (Bailey 1974); percentlie estimators (PCT) were those proposed by Zanakis (1979). The MLB estimators had superior smaller bias and mean square error but larger variance than the PCT estimators. The MLB bias correction in FITTER increased the bias of parameter c, suggesting that for the three-parameter Weibull, the MLB estimators should be used without the correction. Comparisons of predicted percentages indicate that either MLB or PCT estimators, which are simpler to use, can model pine plantations equally well. Forest Sci. 31:260-268.
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Keywords: Fitter; Weibull distribution; diameter distribution; estimation; growth and yield; modeling

Document Type: Journal Article

Affiliations: Mathematical Statistician, USDA Forest Service, Southern Forest Experiment Station, Room T-10210, Postal Services Building, 701 Loyola Avenue, New Orleans, LA 70113

Publication date: 1985-03-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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