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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Bayesian composite quantile regression for the single-index model
Xiaohui Yuan1, Xuefei Xiang2, Xinran Zhang2
1School of Mathematics, Jilin University, Changchun, China.
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.
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