Application of Empirical Bayes/James-Stein Procedures to Simultaneous Estimation Problems in Forest Inventory
Abstract:Traditional estimation procedures may ignore available auxiliary information or use it only in survey design. Such information, however, can be incorporated directly into the estimation process. One such case is where there exist K ≥ 4 groups of simultaneous interest which are homogeneous (similar) with respect to their means. This paper describes James-Stein and empirical Bayes procedures which directly incorporate auxiliary information and thereby improve estimation efficiency as compared to commonly applied normal theory maximum likelihood estimators. Some forest inventory problems provide ideal applications for such estimators. Simulation tests on two forest populations are described. Analysis of results shows consistent reductions in estimator total mean squared error. Forest Sci. 28:753-771.
Document Type: Journal Article
Affiliations: Professor, Department of Forest Resources, College of Forestry, University of Minnesota, St. Paul, MN 55108
Publication date: 1982-12-01
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.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
Also published by SAF:
Journal of Forestry
Other SAF Publications
- Submit a Paper
- Membership Information
- Author Guidelines
- Ingenta Connect is not responsible for the content or availability of external websites