Artículos de revistas
Reduction of Models in the Presence of Nuisance Parameters
Fecha
2009Registro en:
REVISTA COLOMBIANA DE ESTADISTICA, v.32, n.1, p.99-121, 2009
0120-1751
Autor
FARIAS, Rafael
MORENO, German
PATRIOTA, Alexandre
Institución
Resumen
In many statistical inference problems, there is interest in estimation of only some elements of the parameter vector that defines the adopted model. In general, such elements are associated to measures of location and the additional terms, known as nuisance parameters, to control the dispersion and asymmetry of the underlying distributions. To estimate all the parameters of the model and to draw inferences only on the parameters of interest. Depending on the adopted model, this procedure can be both algebraically is common and computationally very costly and thus it is convenient to reduce it, so that it depends only on the parameters of interest. This article reviews estimation methods in the presence of nuisance parameters and consider some applications in models recently discussed in the literature.