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has been cited by the following article:
TITLE: Finite Mixture of Heteroscedastic Single-Index Models
AUTHORS: Peng Zeng
KEYWORDS: EM Algorithm; Finite Mixture Model; Heterogeneity; Heteroscedasticity; Local Linear Smoothing; Single-Index Model
JOURNAL NAME: Open Journal of Statistics, Vol.2 No.1, January 19, 2012
ABSTRACT: In many applications a heterogeneous population consists of several subpopulations. When each subpopulation can be adequately modeled by a heteroscedastic single-index model, the whole population is characterized by a finite mixture of heteroscedastic single-index models. In this article, we propose an estimation algorithm for fitting this model, and discuss the implementation in detail. Simulation studies are used to demonstrate the performance of the algorithm, and a real example is used to illustrate the application of the model.