Journal
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
Volume 48, Issue 5, Pages 1560-1573Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/03610918.2017.1419258
Keywords
Asymmetric Laplace distribution; Gibbs sampling; Mixture quantile regression
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Funding
- National Science Foundation of China [11371227]
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In this paper, we consider the finite mixture of quantile regression model from a Bayesian perspective by assuming the errors have the asymmetric Laplace distribution (ALD), and develop the Gibbs sampling algorithm to estimate various quantile conditional on covariate in different groups using the Normal-Exponential representation of the ALD. We conduct several simulations under different error distributions to demonstrate the performance of the algorithm, and finally apply it to analyse a real data set, finding that the procedure has good performance.
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