A Continuous Threshold Expectile Model.
A Continuous Threshold Expectile Model.
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DOI：
10.1016/j.csda.2017.07.005
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发表时间：
2017-12
影响因子：
1.8
通讯作者：
Li Q
中科院分区：
文献类型：
--
作者：
Zhang F;Li Q
期望回归是探索响应与超出条件均值的解释变量之间关系的有用工具。连续阈值期望回归是为数据建模开发的，其中协变量对响应变量的影响是线性的，但在未知阈值以下和以上以连续的方式变化。使用网格搜索方法获得阈值和回归系数的估计量。导出了所有估计量的渐近性质，并证明了阈值估计量达到根n一致性。针对给定期望值处存在阈值的情况，提出了一种加权CUSUM型检验统计量，并在零模型和局部备选模型下推导了其渐近性质。该检验只需要在没有阈值的情况下在零假设下拟合模型，因此它在计算上比似然比型检验更有效。仿真研究表明，所提出的估计器和测试器在均方差和异方差情况下都具有良好的有限样本性能。将所提出的方法应用于荷兰的增长数据和棒球投手工资数据，揭示了有趣的见解。该方法在R包cthreshER中实现。
Expectile regression is a useful tool for exploring the relation between the response and the explanatory variables beyond the conditional mean. A continuous threshold expectile regression is developed for modeling data in which the effect of a covariate on the response variable is linear but varies below and above an unknown threshold in a continuous way. The estimators for the threshold and the regression coefficients are obtained using a grid search approach. The asymptotic properties for all the estimators are derived, and the estimator for the threshold is shown to achieve root-n consistency. A weighted CUSUM type test statistic is proposed for the existence of a threshold at a given expectile, and its asymptotic properties are derived under both the null and the local alternative models. This test only requires fitting the model under the null hypothesis in the absence of a threshold, thus it is computationally more efficient than the likelihood-ratio type tests. Simulation studies show that the proposed estimators and test have desirable finite sample performance in both homoscedastic and heteroscedastic cases. The application of the proposed method on a Dutch growth data and a baseball pitcher salary data reveals interesting insights. The proposed method is implemented in the R package cthreshER.
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影响因子：
2.7
作者：
Chan, KS;Tsay, RS
通讯作者：
Tsay, RS
影响因子：
1.8
作者：
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影响因子：
1.6
作者：
Haupert, Michael;Murray, James
通讯作者：
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影响因子：
4.5
作者：
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通讯作者：
CHAN, KS
影响因子：
2
作者：
CHAPPELL, R
通讯作者：
CHAPPELL, R