A Computational Bayesian Method for Generalized Semiparametric Regression Models

DOI10.1080/03610918.2014.948192zbMath1341.62239OpenAlexW1975400416MaRDI QIDQ3178514

Minjung Kyung

Publication date: 14 July 2016

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2014.948192

zbMATH Keywords

semiparametric regressionMetropolis-Hastings algorithmGibbs samplingsurvey datageneralized linear mixed modelshierarchical modelsmultinomial-Dirichlet distributionempirical studies of soft power in Asiasoft power shift

Mathematics Subject Classification ID

Bayesian inference (62F15) Generalized linear models (logistic models) (62J12)

Cites Work

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• Sampling schemes for generalized linear Dirichlet process random effects models
• Additive cubic spline regression with Dirichlet process mixture errors
• On conditional variance estimation in nonparametric regression
• Linear and generalized linear mixed models and their applications.
• Estimation in Dirichlet random effects models
• A computational Bayesian method for estimating the number of knots in regression splines
• Bayesian curve-fitting with free-knot splines
• On scale mixtures of normal distributions
• Generalized linear mixed models a pseudo-likelihood approach

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