Confidence regions in singular weakly nonlinear regression models with constraints

Year, pages: 2016, 287 - 304

It is rather complicated to construct the confidence region in nonlinear regression model mainly when number of parameters is large. If the nonlinearity of the model is weak, then it is possible, after some modification, to approximate the confidence region by a confidence ellipsoid in the linearized model. The aim of the paper is to propose a solution in singular models with constraints.

Kubáček, L. 2016. Confidence regions in singular weakly nonlinear regression models with constraints. In Mathematica Slovaca, vol. 66, no.1, pp. 287-304. 0139-9918. DOI: https://doi.org/10.1515/ms-2015-0136

Kubáček, L. (2016). Confidence regions in singular weakly nonlinear regression models with constraints. Mathematica Slovaca, 66(1), 287-304. 0139-9918. DOI: https://doi.org/10.1515/ms-2015-0136