CONFIDENCE CURVES FOR A FUNCTION OF PARAMETERS IN NONLINEAR REGRESSION

  • Published : 2003.03.01

Abstract

We consider obtaining graphical summaries of uncertainty in estimates of parameters in nonlinear models. A nonlinear constrained optimization algorithm is developed for likelihood based confidence intervals for the functions of parameters in the model The results are applied to the problem of finding significance levels in nonlinear models.

Keywords

References

  1. Journal of the Royal Statistical Society v.B42 Relative curvature measures of nonlinearity(with discussion) Bates, D. M.;Watts, D. G.
  2. The Annals of Statistics v.9 Parameter transformations for improved approximate confidence regions in nonlinear least squares Bates, D. M.;Watts, D. G.
  3. Nonlinear Regression Analysis and Its Application Bates, D. M.;Watts, D. G.
  4. Journal of the Royal Statistical Society v.B22 Confidence regions in nonlinear estimation(with discussion) Beale, E. M. L.
  5. Journal of the American Statistical Association v.82 Approximate confidence limits for a parameter function in nonlinear regression Clarke, G. P. Y.
  6. Journal of the American Statistical Association v.85 Confidence curves in nonlinear regression Cook, R. D.;Weisberg, S.
  7. Technometrics v.29 Computational experiences for confidence regions and confidence intervals for nonlinear least squares Donaldson, J. R.;Schnabel, R. B.
  8. Practical Methods of Optimization(2nd ed) Fletcher, R.
  9. practical Optimization Gill, P. E.;Murray, W.;Wright, M. H.
  10. Linear and Nonlinear Programming(2nd ed) Luenberger, D. G.
  11. Nonlinear Regression Seber, G. A. F.;Wild, C. J.
  12. Differential Geometry Stoker, J. J.