Notes: Approximating the Precision of the Parameter Estimates of a Nonlinear Model Prior to Sampling
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.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
Document Type: Miscellaneous
Affiliations: Assistant Professor of Forest Biometrics, Department of Forestry, 110 Mumford Hall, University of Illinois, Urbana, IL 61801
Publication date: 1984-09-01
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
- Submit a Paper
- Membership Information
- Author Guidelines
- Ingenta Connect is not responsible for the content or availability of external websites