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Characterizing Diameter Distributions with Modified Data Types and Forms of the Weibull Distribution

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Complete, left censored, and left truncated data fitted with a two-parameter complete Weibull distribution were compared for characterizing complete diameter distributions. The complete data provided the best fit, followed by the censored and truncated data. As the intensity of censoring and truncation increased distribution description was generally poorer. The use of left truncated data was judged unacceptable. Left censored data appears to be a reasonable alternative to complete data. In field applications collection of left censored data would reduce measurement time. Complete, left censored, and left truncated data fitted with a two-parameter complete Weibull and left truncated data fitted with a two-parameter left truncated Weibull were compared for characterizing left truncated diameter distributions. The left truncated data fitted with a left truncated Weibull performed best, but no data type-distribution combination worked well for inverse j-shape distributions. Forest Sci. 32:37-48.

Keywords: Censored data; truncated data

Document Type: Journal Article

Affiliations: Principal Mensurationist, USDA Forest Service, Southern Forest Experiment Station, Monticello, AR 71655

Publication date: March 1, 1986

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
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