Semiparametric two-component mixture model with a known component: An asymptotically normal estimator
Laurent Bordes, Pierre Vandekerkhove · Mathematical Methods of Statistics · 2010
In this paper we consider a two-component mixture model, one component of which has a known distribution while the other is only known to be symmetric. The mixture proportion is also an unknown parameter of the model. This mixture model class has proved to be useful to analyze gene expression data coming from microarray analysis. In this paper a general estimation method is proposed leading to a joint central limit result for all the estimators. Applications to basic testing problems related to this class of models are proposed, and the corresponding inference procedures are illustrated through some simulation studies.