Finite mixture models have offered a very important tool for exploring complex data
structures in many scientific areas, such as economics, epidemiology and finance …

Identifiability of nonparametric mixture models and Bayes optimal clustering Page 1 The
Annals of Statistics 2020, Vol. 48, No. 4, 2277–2302 https://doi.org/10.1214/19-AOS1887 © …

We review the theory on semiparametric hidden Markov models (HMMs), that is, HMMs for
which the state‐dependent distributions are not fully parametrically, but rather semi‐or …

We study a two-component semiparametric mixture model where one component
distribution belongs to a parametric class, while the other is symmetric but otherwise …

Mixture models are a powerful tool for analyzing complex and heterogeneous datasets
across many scientific fields, from finance to genomics. Mixture Models: Parametric …

Motivated by the analysis of a Positron Emission Tomography (PET) imaging data
considered in Bowen et al.[Radiother. Oncol. 105 (2012) 41–48], we introduce a …

We investigate a flexible two-component semiparametric mixture of regressions model, in
which one of the conditional component distributions of the response given the covariate is …

A Selective Overview of Semiparametric Mixture of Regression Models | SpringerLink Skip to
main content Advertisement SpringerLink Account Menu Find a journal Publish with us Track …

In this thesis, we develop theoretical tools to examine estimators in non-parametric
regression models in regard of uniform convergence rates and uniform adaptivity with …