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Approximate Srivastava Estimation in Forestry

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Srivastava estimation formalizes the introduction of additional prior and posterior information in sampling to increase efficiency in estimation. An unbiased new estimator is given for Poisson sampling which is approximately as efficient as the standard slightly biased estimator without using any additional information. The increased efficiency possible with this method or approximations to it are illustrated for Poisson sampling and point-Poisson sampling using simulations. Srivastava estimation may be applicable in many forest inventory situations. Besides efficiency, the seriousness of estimation bias and reliability of variance estimators need to be considered in all applications. FOR. SCI. 39(2):309-320.
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Keywords: Poisson sampling; estimation bias

Document Type: Journal Article

Affiliations: Project Leader, USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO 80526

Publication date: 1993-05-01

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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