Testing error heterogeneity in censored linear regression
Testing error heterogeneity in censored linear regression
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DOI：
10.1016/j.csda.2021.107207
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发表时间：
2021-03
期刊：
影响因子：
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通讯作者：
Caiyun Fan;Wenbin Lu;Yong Zhou
中科院分区：
文献类型：
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作者：
Caiyun Fan;Wenbin Lu;Yong Zhou
在删减线性回归中，一个关键的假设是误差与预测因子无关。我们开发了一种综合检验来检验删节线性回归的误差异质性。我们的方法是基于在一个工作的核机回归模型中测试方差成分。所提出的检验统计量的极限零分布显示为具有一个自由度的独立卡方分布的加权和。推导了一种近似零分布的重采样方案。通过仿真和两个真实数据集对所提出的测试的经验性能进行了评估。
In censored linear regression, a key assumption is that the error is independent of predictors. We develop an omnibus test to check error heterogeneity in censored linear regression. Our approach is based on testing the variance component in a working kernel machine regression model. The limiting null distribution of the proposed test statistic is shown to be a weighted sum of independent chi-squared distributions with one degree of freedom. A resampling scheme is derived to approximate the null distribution. The empirical performance of the proposed tests is evaluated via simulation and two real data sets.