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- W2053152045 abstract "A Reversible Jump Markov chain Monte Carlo approach is proposed for non-parametric quantile regression estimation by a sequence of piecewise polynomials. Two methods or algorithms under the proposed approach are presented for computing both the number and locations of the knots of a piecewise polynomial. It is shown empirically that the proposed approach works reasonably well on a wide range of quantile regression function examples, using both real and artificial data sets. This research is also an extension of Bayesian piecewise polynomial approach on standard mean regression estimation to quantile regression estimation." @default.
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- W2053152045 date "2002-08-01" @default.
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- W2053152045 title "Quantile regression using RJMCMC algorithm" @default.
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- W2053152045 doi "https://doi.org/10.1016/s0167-9473(01)00093-7" @default.
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