Notes: Approximating the Precision of the Parameter Estimates of a Nonlinear Model Prior to Sampling
Abstract:Using approximations based on the methods and theories of linear least squares, a procedure is presented for estimating the variance of the parameter estimates of a nonlinear time dependent growth model before sampling for growth. To use the procedure, prior knowledge is needed of the approximate model parameter values and the variance about the regression. An example is given where the relative standard error of the asymptote of the Chapman-Richards function is estimated for increasing growth series lengths. Forest Sci. 30:836-841.
Document Type: Miscellaneous
Affiliations: Assistant Professor of Forest Biometrics, Department of Forestry, 110 Mumford Hall, University of Illinois, Urbana, IL 61801
Publication date: September 1, 1984
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