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Estimation of the Diameter Increment Function or Other Tree Relations Using Angle-Count Samples

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A formula is derived for the bias when an angle-count sample is used to estimate the mean of a tree variable that is correlated with the breast height diameter. This bias occurs, for instance, if average increment is estimated with increment cores from an angle-count sample. Estimation of mean increment for a given initial diameter is studied further by assuming that increments are log-normally distributed, in which case the sampling distribution is a mixture of three log-normal distributions. An estimate obtained by weighting observations inversely to the basal area (i.e., with the estimated tree frequency) compares favorably in simulations with a parametric estimate derived from the sampling distribution of diameters. If increments are regressed on the initial diameters, then weighting proportionally to the initial basal area and inversely to the current basal area gives smaller bias and standard deviation of parameter estimates than weighting inversely to the current basal area alone. For. Sci. 33(3):725-739.

Keywords: Increment cores; log-normal distribution; mixture distribution; weighted estimate

Document Type: Journal Article

Affiliations: Professor of Forest Management and Biometrics, School of Forest Resources, The University of Georgia, Athens, GA 30602

Publication date: September 1, 1987

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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