Quantile regression when the covariates are functions
Quantile regression when the covariates are functions
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DOI：
10.1080/10485250500303015
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发表时间：
2005-10-01
影响因子：
1.2
通讯作者：
Sarda, P
中科院分区：
文献类型：
--
作者：
Cardot, H;Crambes, C;Sarda, P
本文讨论了解释变量在函数空间取值且响应为标量时分位数线性回归模型。我们提出了一个样条估计的功能系数，最大限度地减少了惩罚L-1型标准。然后，我们研究了该估计量的渐近性态。惩罚性是获得解的存在性和收敛性的首要条件。
This article deals with a linear model of regression on quantiles when the explanatory variable takes values in some functional space and the response is scalar. We propose a spline estimator of the functional coefficient that minimizes a penalized L-1 type criterion. Then, we study the asymptotic behavior of this estimator. The penalization is of primary importance to get existence and convergence.