Variational approximation for heteroscedastic linear models and matching pursuit algorithms

DOI10.1007/s11222-011-9243-2zbMath1322.62031arXiv1011.4832OpenAlexW3125364414MaRDI QIDQ746230

Chenlei Leng, Minh-Ngoc Tran, David J. Nott

Publication date: 16 October 2015

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1011.4832

zbMATH Keywords

heteroscedasticityBayesian model selectionvariational approximationmatching pursuit

Mathematics Subject Classification ID

Linear regression; mixed models (62J05)

Related Items

Variational inferences for partially linear additive models with variable selection, Adaptive Metropolis-Hastings sampling using reversible dependent mixture proposals, Flexible multivariate regression density estimation, Simultaneous variable selection and component selection for regression density estimation with mixtures of heteroscedastic experts, Heteroscedastic additive models - Estimating the fixed effects and covariance matrix parameters, Robust estimation and variable selection in heteroscedastic linear regression, Variational Inference for Heteroscedastic Semiparametric Regression

Uses Software

• alr3
• SemiPar
• GAMLSS
• PRMLT

Cites Work

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