Constrained design strategies for improving normal approximations in nonlinear regression problems

Journal of Statistical Planning and Inference

Volumn 104, Issue 1, 2002, Pages 175-196

  Clyde, Merlise ^a   Chaloner, Kathryn ^b  

^a DUKE UNIVERSITY   (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

Author keywords

Bayesian methods; Curvature measures; Optimal design

Indexed keywords

EID: 0036568358     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0378-3758(01)00239-7     Document Type: Article

References (44)

1. Relative curvature measures of nonlinearity
2. Nonlinear Regression Analysis and its Applications
3. Confidence regions in non-linear estimation
4. Design of experiments in nonlinear situations
5. Transformations of the independent variables
6. A note on optimal Bayesian design for nonlinear problems
7. Optimal Bayesian design applied to logistic regression experiments
8. Bayesian design: A review
9. Locally optimal designs for estimating parameters
10. Marginal curvatures and their usefulness in the analysis of nonlinear regression models
11. Optimal designs for models incorporating the Richards function
12. Bayesian optimal designs for approximate normality
13. An object-oriented system for Bayesian nonlinear design using xlisp-stat
14. Bayesian optimal designs for approximate normality
15. Equivalence of constrained and weighted designs in multiple objective design problems
16. Experiments for Nonlinear functions
17. A note on parameter-effects curvature
18. Multivariate Statistics: A Vector Space Approach
19. 1975 Defining the curvature of a statistical problem (with applications to second order efficiency) (with discussion)
20. Recent advances in nonlinear experimental designs
21. User's guide for NPSOL (Version 4.0): A Fortran package for nonlinear programming
22. A quadratic design criterion for precise estimation in nonlinear regression models
23. Parameterization issues in Bayesian inference
24. The Analysis of Linear Models
25. Parameterizations of non-linear models
26. The appropriateness of the asymptotic distribution in a nonlinear regression model in relation to curvature
27. Curvature adjusted optimal nonlinear designs for correlated responses
28. The geometry of asymptotic inference (with discussion)
29. Some diagnostics of maximum likelihood and posterior non-normality
30. The equivalence of two extremum problems
31. Tensor Methods in Statistics
32. Discussion of "Defining the curvature of a statistical problem (with applications to second order efficiency)"
33. A note on quadratic designs for nonlinear regression models
34. Nonlinear Statistical Models
35. Nonlinear experimental design based on the distribution of estimators
36. Nonlinear experimental design for constrained LS estimation
37. Second order approximation of the entropy in nonlinear least-squares estimation
38. On linear regression designs which maximize information
39. Curvature and convergence
40. Lisp-Stat, an Object-Oriented Environment for Dynamic Graphics
41. Bayesian experimental design for the analysis of another Bayesian (or of a frequentist)
42. Some general points in the theory and construction of D-optimum experimental designs
43. Tensor Spaces and Exterior Algebra