Physical Sciences and Mathematics Commons^™

Alternative Procedures For Estimation Of Nonlinear Regression Parameters, William J. Price, Bahman Shafii

Conference on Applied Statistics in Agriculture

Biological research data are often represented using nonlinear model specifications that lend themselves to the testing of relevant hypotheses concerning the model parameters. This is typically achieved with classical nonlinear least squares techniques such as Gauss-Newton or Levenberg-Marquardt which allow for both the estimation and inference phases of the analysis. Under some circumstances, however, sensitivity to data or model specifications may lead these methods to fail convergence tests or exhibit nonlinearity in the parameter estimates, which will in turn limit the usefulness of inferential results. In such cases, other estimation methods may present a means of avoiding these problems while …