A semiparametric Bayesian approach to generalized partial linear mixed models for longitudinal data

DOI10.1016/J.CSDA.2012.03.018zbMath1255.62120OpenAlexW2045595693WikidataQ57535724 ScholiaQ57535724MaRDI QIDQ1927222

Xing-De Duan, Nian Sheng Tang

Publication date: 30 December 2012

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

Full work available at URL: https://doi.org/10.1016/j.csda.2012.03.018

zbMATH Keywords

Bayes factorGibbs samplerMetropolis-Hastings algorithmDirichlet process priorP-splinesgeneralized partial linear mixed models

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Numerical computation using splines (65D07) Bayesian inference (62F15) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (7)

Bayesian quantile semiparametric mixed-effects double regression models ⋮ Nonparametric tests for panel count data with unequal observation processes ⋮ A semiparametric Bayesian approach to binomial distribution logistic mixed-effects models for longitudinal data ⋮ Bayesian quantile regression and variable selection for partial linear single-index model: Using free knot spline ⋮ Semiparametric Bayesian inference on generalized linear measurement error models ⋮ Bayesian analysis of joint mean and covariance models for longitudinal data ⋮ Bayesian estimation and influence diagnostics of generalized partially linear mixed-effects models for longitudinal data

Uses Software

• SemiPar
• tsbridge

Cites Work

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