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- W2562019904 abstract "In this paper, we adopt the Bayesian approach to expectile regression employing a likelihood function that is based on an asymmetric normal distribution. We demonstrate that improper uniform priors for the unknown model parameters yield a proper joint posterior. Three simulated data sets were generated to evaluate the proposed method which show that Bayesian expectile regression performs well and has different characteristics comparing with Bayesian quantile regression. We also apply this approach into two real data analysis." @default.
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- W2562019904 date "2016-05-31" @default.
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- W2562019904 title "Bayesian expectile regression with asymmetric normal distribution" @default.
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- W2562019904 doi "https://doi.org/10.1080/03610926.2015.1088030" @default.
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