Introduction Diabetes is a chronic metabolic disease characterized by high levels of blood
glucose, which can lead over time to severe impairment to the heart, blood vessels, eyes …

This article presents basic ideas of finite mixture models in which the number of components
is known and the distributions comprising the components are not assumed to come from …

With the rapid development of metro systems, it has become increasingly important to study
phenomena such as passenger flow distribution and passenger boarding behavior. It is …

Huber's contaminated model is a basic model for data with outliers. This paper aims at
addressing several fundamental problems about this model. We first study its identifiability …

A new class of semiparametric mixture regression models with covariate-varying mixing
proportions is introduced by embedding machine learning methods into mixtures of …

In this article, we propose two classes of semiparametric mixture regression models with
single-index for model based clustering. Unlike many semiparametric/nonparametric mixture …

Two-sample contamination model test Page 1 Bernoulli 30(1), 2024, 170–197 https://doi.org/10.3150/23-BEJ1593
Two-sample contamination model test XAVIER MILHAUD1,a, DENYS POMMERET2,b …

Accurate quantification of nanoparticle fractions in polydisperse mixture is challenging for
many analytical techniques. For single particle inductively coupled plasma mass …

In fitting a mixture of linear regression models, normal assumption is traditionally used to
model the error and then regression parameters are estimated by the maximum likelihood …

In this work, we investigate the $ K $-sample clustering of populations subject to
contamination phenomena. A contamination model is a two-component mixture model …