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Multiple-Occasion Partial Replacement Sampling for Growth Components

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Abstract:

The Ware and Cunia (1962) method for estimating volume at time 2 from sampling with partial replacement is proven to be equivalent to a generalized least squares estimator (GLS). The GLS approach is advantageous because it extends easily to encompass multiple occasion sampling with partial replacement (MOSPR). An iterative GLS procedure is given for simultaneously estimating population parameters and their variances that avoids incompatibility problems that arose with some previously published methods. The MOSPR theory is also extended to include growth component estimation with additivity constraints. For. Sci. 35(2):388-400.

Keywords: Generalized least squares; maximum likelihood; mixed estimation

Document Type: Journal Article

Affiliations: Mathematical Statistician, USDA Forest Service, Southern Forest Experiment Station, New Orleans, LA. 70113.

Publication date: June 1, 1989

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  • 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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