Approximation of probability density functions via location-scale finite mixtures in Lebesgue spaces
From MaRDI portal
Publication:6169393
DOI10.1080/03610926.2021.2002360arXiv2008.09787OpenAlexW3081275934MaRDI QIDQ6169393
Geoffrey J. McLachlan, Faicel Chamroukhi, Hien Duy Nguyen, TrungTin Nguyen
Publication date: 11 July 2023
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2008.09787
Approximations to statistical distributions (nonasymptotic) (62E17) Approximation by other special function classes (41A30)
Related Items (2)
Universal approximation on the hypersphere ⋮ A non-asymptotic approach for model selection via penalization in high-dimensional mixture of experts models
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Universal series induced by approximate identities and some relevant applications
- Applied functional analysis. Functional analysis, Sobolev spaces and elliptic differential equations
- Constructive methods of approximation by ridge functions and radial functions
- Real analysis: measures, integrals and applications
- Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models
- Finite mixture and Markov switching models.
- Mixtures
- Approximation of probability distributions by convex mixtures of Gaussian measures
- Handbook of Mixture Analysis
- Approximation by finite mixtures of continuous density functions that vanish at infinity
This page was built for publication: Approximation of probability density functions via location-scale finite mixtures in Lebesgue spaces