Empirical Bayes Development of Honduran Pine Yield Models
Authors: Green, Edwin J.; Strawderman, William E.; Thomas, Charles E.
Source: Forest Science, Volume 38, Number 1, 1 February 1992 , pp. 21-33(13)
Publisher: Society of American Foresters
Abstract:Occasionally it is of interest to calibrate a given growth or yield model to data from several regions. If it is expected that the parameters from different regions can somehow be regarded as similar, then a Bayesian approach suggests itself. A cursory examination of the literature reveals that most of the theoretical work on empirical Bayes estimation for the linear model has focused on simultaneously estimating the coefficients in one model. In these methods the usual least squares estimates of the model parameters are shrunk toward their mean. One set of parameter estimates results. In contrast we desire a method whereby multiple sets of parameter estimates are produced. We report the results of using such a method to calibrate yield models for unthinned Honduran pine plantations to data from 21 soil-site groups. The models compare favorably to those developed via traditional methods and allow estimation of regression coefficients even for soil-site groups for which the design matrix is not of full rank. For. Sci. 38(1):21-33.
Document Type: Journal Article
Affiliations: Research Forester, Institute for Quantitative Studies, South For. Exp. Stn., 701 Loyola Avenue, New Orleans, LA 70113
Publication date: 1992-02-01
- 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.
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