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Precision of Total Volume Estimates Resulting from Pseudo-Bayes Estimator for Stock Tables

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In an earlier article we presented a novel estimator for stand tables. The estimator performed much better than the usual estimator in simulation studies. In this article we extend the method to volume estimation, and demonstrate via simulation studies that total volume estimates from the pseudo-Bayes stand table estimator are superior to estimates derived from the usual stand table estimator. We also derive estimates for the variance and mean squared error of the pseudo-Bayes total volume estimator and approximate confidence intervals. The intervals based on the mean squared error have approximately correct coverage and are narrower than the usual confidence intervals.
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Keywords: Bayesian inference; loblolly pine; volume estimation

Document Type: Research Article

Publication date: 2008-04-01

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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.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

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    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
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