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Confidence regions in nonlinear models with constraints. (English) Zbl 1046.62065
Summary: There are some difficulties in construction of confidence regions in nonlinear models with constraints. Even if an exact algorithm (in the case of normality) can be derived, the numerical calculation is rather tedious. Thus if a simple algorithm can be find it will be preferred in practice. The aim of the paper is to find a simple criterion which enables us to decide whether it is possible to use algorithms useful in linear models.

MSC:
62J02 General nonlinear regression
62F30 Parametric inference under constraints
62F25 Parametric tolerance and confidence regions
62H12 Estimation in multivariate analysis
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