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Flexible Bayesian quantile regression for nonlinear mixed effects models based on the generalized asymmetric Laplace distribution.
- Source :
-
Journal of Statistical Computation & Simulation . Oct2023, Vol. 93 Issue 15, p2725-2750. 26p. - Publication Year :
- 2023
-
Abstract
- We propose flexible Bayesian quantile regression for a class of parametric nonlinear mixed effects models for longitudinal data based on the generalized asymmetric Laplace distribution, which exhibits more flexibility in skewness, mode and tail behaviour than the frequently used asymmetric Laplace distribution in quantile regression. An efficient Markov chain Monte Carlo procedure based on the adaptive random walk Metropolis-within-Gibbs sampling algorithm is derived for posterior inference. We demonstrate through simulation studies and empirical analysis that the proposed method could provide more accurate parameter estimation and better model fit than the existing methods. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00949655
- Volume :
- 93
- Issue :
- 15
- Database :
- Academic Search Index
- Journal :
- Journal of Statistical Computation & Simulation
- Publication Type :
- Academic Journal
- Accession number :
- 172045963
- Full Text :
- https://doi.org/10.1080/00949655.2023.2204437