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Simple Methods of Estimating Certain Nonlinear Functions, With Emphasis on Agricultural Data

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  • Day, Richard H.

Abstract

Excerpt from the report Introduction: This paper presents two elementary methods for fitting three different nonlinear functions to empirical data by means of simple linear regression. Iterative least squares methods which have been developed for estimating parameters of nonlinear functions sometimes lead to certain difficulties in application. Because this is the case the much simpler methods developed in this handbook are useful tools for application. The relative merits of this approach versus the nonlinear iterative approach are briefly described in the concluding-section. The Spillman, Gompertz, and Pearl-Reed (logistic) functions are considered. The two methods presented for the Pearl-Reed function are already well known and are given first. Then analogous methods are derived for the Spillman and the closely related Gompertz curves; these apparently have not been presented in the literature.

Suggested Citation

  • Day, Richard H., 1963. "Simple Methods of Estimating Certain Nonlinear Functions, With Emphasis on Agricultural Data," Miscellaneous Publications 305829, United States Department of Agriculture, Economic Research Service.
    • Handle: RePEc:ags:uersmp:305829
    DOI: 10.22004/ag.econ.305829
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    References listed on IDEAS

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    1. Burton L. French, 1956. "Functional Relationships for Irrigated Corn Response to Nitrogen," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 38(3), pages 736-747.
    2. Spillman, W. J., 1933. "Use of the Exponential Yield Curve in Fertilizer Experiments," Technical Bulletins 163535, United States Department of Agriculture, Economic Research Service.
    3. Paschal, J.L. & French, B.L., 1956. "A Method of Economic Analysis Applied to Nitrogen Fertilizer Rate Experiments on Irrigated Corn," Technical Bulletins 157132, United States Department of Agriculture, Economic Research Service.
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    Research Methods/ Statistical Methods;

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