The important role of finite mixture models in the statistical analysis of data is underscored
by the ever-increasing rate at which articles on mixture applications appear in the statistical …

Clustering is the task of automatically gathering observations into homogeneous groups,
where the number of groups is unknown. Through its basis in a statistical modeling …

Finite mixture models are being used increasingly to model a wide variety of random
phenomena for clustering, classification and density estimation. mclust is a powerful and …

Claudin-low breast cancers are aggressive tumors defined by the low expression of key
components of cellular junctions, associated with mesenchymal and stemness features …

Abstract Model-based clustering is a popular approach for clustering multivariate data which
has seen applications in numerous fields. Nowadays, high-dimensional data are more and …

In their natural environments, microorganisms mainly operate at suboptimal growth
conditions with fluctuations in nutrient abundance. The resulting cellular adaptation is …

Segmentation studies are crucial for planning sustainability strategies, and tourists'
perceptions of destinations offer important segmentation criteria. The aim of this study is to …

A mixture of multivariate contaminated normal distributions is developed for model‐based
clustering. In addition to the parameters of the classical normal mixture, our contaminated …

ABSTRACT A high level of production at the peak of lactation may be associated with animal
health disorders, high feeding costs, and reduced milk supply throughout the year. The …

We herein propose an atlas of 32 sentence-related areas based on a 3-step method
combining the analysis of activation and asymmetry during multiple language tasks with …