Skip to main content

An Evaluation of Percentile and Maximum Likelihood Estimators of Weibull Parameters

Buy Article:

$29.50 plus tax (Refund Policy)


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.

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: March 1, 1985

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.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
  • Submit a Paper
  • Membership Information
  • Author Guidelines
  • Ingenta Connect is not responsible for the content or availability of external websites

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more