Nonparametric estimation of conditional quantiles using quantile regression trees ∗ ( Published in Bernoulli ( 2002 ) , 8 , 561 – 576 )
Nonparametric estimation of conditional quantiles using quantile regression trees ∗ ( Published in Bernoulli ( 2002 ) , 8 , 561 – 576 )
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使用分位数回归树对条件分位数进行非参数估计*（发表于 Bernoulli (2002), 8, 561 – 576）
DOI：
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发表时间：
2008
期刊：
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通讯作者：
P. Chaudhuri
中科院分区：
文献类型：
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作者：
P. Chaudhuri
A nonparametric regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning of the covariate space is investigated. Unlike least squares regression trees, which concentrate on modeling the relationship between the response and the covariates at the center of the response distribution, our quantile regression trees can provide insight into the nature of that relationship at the center
