Understanding the effect of measurement error on quantile regressions
Understanding the effect of measurement error on quantile regressions
复制标题
了解测量误差对分位数回归的影响
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
A. Chesher
中科院分区：
文献类型：
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作者：
A. Chesher
利用小方差近似方法研究了解释变量的测量误差对分位数回归函数的影响。该近似显示了误差污染和无误差分位数回归函数是如何相关的。一个关键因素是无误差解释变量的分布。精确的计算可检验近似值的准确性.如果用易于估计的误差污染解释变量的密度代替无误差解释变量的密度，则近似误差的阶数不变。然后，可以使用近似来研究估计值对测量误差的变化量的敏感性。
The impact of measurement error in explanatory variables on quantile regression functions is investigated using a small variance approximation. The approximation shows how the error contaminated and error free quantile regression functions are related. A key factor is the distribution of the error free explanatory variable. Exact calculations probe the accuracy of the approximation. The order of the approximation error is unchanged if the density of the error free explanatory variable is replaced by the density of the error contaminated explanatory variable which is easily estimated. It is then possible to use the approximation to investigate the sensitivity of estimates to varying amounts of measurement error.