REGRESSION RANK SCORES AND REGRESSION QUANTILES
REGRESSION RANK SCORES AND REGRESSION QUANTILES
复制标题
DOI：
10.1214/aos/1176348524
复制
发表时间：
1992-03-01
影响因子：
4.5
通讯作者：
JURECKOVA, J
中科院分区：
文献类型：
--
作者：
GUTENBRUNNER, C;JURECKOVA, J
我们发现，回归分位数，这可以计算为线性规划问题的解决方案，以及相应的对偶问题的解决方案，我们称之为回归秩分数，推广的对偶顺序统计量和秩的线性模型的位置。注意到这一事实，我们研究了异方差线性回归模型中的回归分位数和回归秩-分数过程，得到了一些新的估计量和与现有估计量的有趣比较。
We show that regression quantiles, which could be computed as solutions of a linear programming problem, and the solutions of the corresponding dual problem, which we call the regression rank-scores, generalize the duality of order statistics and of ranks from the location to the linear model. Noting this fact, we study the regression quantile and regression rank-score processes in the heteroscedastic linear regression model, obtaining some new estimators and interesting comparisons with existing estimators.