Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to use computational tools. The aim of the paper is to illustrate the potential of these methods in the framework of nonlinear regression and give insight into how they can be implemented into S-Plus.
Higher-Order Likelihood-Based Inference in Nonlinear Regression
BRAZZALE, ALESSANDRA ROSALBA
1999
Abstract
Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to use computational tools. The aim of the paper is to illustrate the potential of these methods in the framework of nonlinear regression and give insight into how they can be implemented into S-Plus.File in questo prodotto:
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