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.
Proceedings of the 14th International Workshop on Statistical Modelling
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/181228
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