Bayesian composite quantile regression for the single-index model.
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- Record sourced from PubMed, PMID 37163496.
- Also identified by DOI 10.1371/journal.pone.0285277 and PMC identifier 10171657.
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Abstract
By using a Gaussian process prior and a location-scale mixture representation of the asymmetric Laplace distribution, we develop a Bayesian analysis for the composite quantile single-index regression model. The posterior distributions for the unknown parameters are derived, and the Markov chain Monte Carlo sampling algorithms are also given. The proposed method is illustrated by three simulation examples and a real dataset.
Medical subject headings
- Algorithms