Laplace mixture of linear experts

DOI10.1016/j.csda.2014.10.016zbMath1468.62147OpenAlexW2085831769MaRDI QIDQ1660202

Geoffrey J. McLachlan, Hien Duy Nguyen

Publication date: 15 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2014.10.016

zbMATH Keywords

mixture of expertsrobust regressionLaplace distributionminorization-maximization algorithm

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) General nonlinear regression (62J02)

Related Items (18)

Laplace mixture autoregressive models ⋮ Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models ⋮ Mixture of linear experts model for censored data: a novel approach with scale-mixture of normal distributions ⋮ Robust fitting of mixture models using weighted complete estimating equations ⋮ Linear mixed models with marginally symmetric nonparametric random effects ⋮ Maximum likelihood estimation of triangular and polygonal distributions ⋮ Editorial: The third special issue on advances in mixture models ⋮ Robust variable selection in finite mixture of regression models using the t distribution ⋮ A globally convergent algorithm for Lasso-penalized mixture of linear regression models ⋮ Gibbs sampling for mixture quantile regression based on asymmetric Laplace distribution ⋮ New estimation in mixture of experts models using the Pearson type VII distribution ⋮ Robust mixture of experts modeling using the \(t\) distribution ⋮ Component selection for exponential power mixture models ⋮ A Universal Approximation Theorem for Mixture-of-Experts Models ⋮ Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Models ⋮ Heteroscedastic Laplace mixture of experts regression models and applications ⋮ Grouped Heterogeneous Mixture Modeling for Clustered Data ⋮ Latent mixture modeling for clustered data

Uses Software

• R
• flexmix
• robustbase

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Time series modeling by a regression approach based on a latent process
• Model-based clustering and segmentation of time series with changes in regime
• Semiparametric mixtures of regressions
• Robust mixture regression model fitting by Laplace distribution
• Local statistical modeling via a cluster-weighted approach with elliptical distributions
• On mixtures of skew normal and skew \(t\)-distributions
• Fitting finite mixtures of generalized linear regressions in \textsf{R}
• Estimating the dimension of a model
• Robust mixture regression using the \(t\)-distribution
• A multivariate linear regression analysis using finite mixtures of \(t\) distributions
• Model-based clustering via linear cluster-weighted models
• The EM Algorithm and Extensions, 2E
• Concomitant variables in finite mixture models
• Estimation of a semiparametric mixture of regressions model
• Identifiability of Finite Mixtures of Elliptical Distributions
• Robust Statistics
• On the Identifiability of Finite Mixtures
• Robust Estimation of Straight Line Regression Coefficients by Minimizing pth Power Deviations
• Optimization
• Robust Statistics
• A new look at the statistical model identification

This page was built for publication: Laplace mixture of linear experts