Quantiles, expectiles and splines
Quantiles, expectiles and splines
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DOI：
10.1016/j.jeconom.2009.01.001
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发表时间：
2009-10-01
影响因子：
6.3
通讯作者：
Harvey, Andrew
中科院分区：
文献类型：
--
作者：
De Rossi, Giuliano;Harvey, Andrew
时变分位数可以通过为相应的总体分位数制定时间序列模型并迭代地应用适当修改的状态空间信号提取算法来拟合。它表明，这样的分位数满足固定分位数的定义属性，具有适当的观察以上和以下。与分位数一样，时变期望值可以通过状态空间信号提取算法来估计，并且它们满足与固定期望值相关联的矩条件的推广性质。由于状态空间形式可以处理不规则间隔的观察，所提出的算法可以适用于提供一个可行的手段计算基于样条的非参数分位数和期望回归。(C)2009爱思唯尔有限公司版权所有。
A time-varying quantile can be fitted by formulating a time series model for the corresponding population quantile and iteratively applying a suitably modified state space signal extraction algorithm. It is shown that such quantiles satisfy the defining property of fixed quantiles in having the appropriate number of observations above and below. Like quantiles, time-varying expectiles can be estimated by a state space signal extraction algorithm and they satisfy properties that generalize the moment conditions associated with fixed expectiles. Because the state space form can handle irregularly spaced observations, the proposed algorithms can be adapted to provide a viable means of computing spline-based non-parametric quantile and expectile regressions. (C) 2009 Elsevier B.V. All rights reserved.