REGRESSION RANK SCORES AND REGRESSION QUANTILES

被引：141

作者：

GUTENBRUNNER, C ^{[1
]}

JURECKOVA, J ^{[1
]}

机构：

[1] CHARLES UNIV, DEPT PROBABIL & STAT, CS-18600 PRAGUE 8, CZECHOSLOVAKIA

来源：

ANNALS OF STATISTICS | 1992年 / 20卷 / 01期

关键词：

REGRESSION QUANTILE; REGRESSION RANK-SCORE; TRIMMED LEAST-SQUARES ESTIMATOR; L-STATISTIC; LINEAR RANK STATISTIC;

D O I：

10.1214/aos/1176348524

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页码：305 / 330

页数：26

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