REGRESSION RANK SCORES AND REGRESSION QUANTILES

• 成果类型: Article
• 署名作者: GUTENBRUNNER, C; JURECKOVA, J
• 署名单位: Charles University Prague
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176348524
• 发表日期: 1992
• 页码: 305-330
• 关键词: linear-model

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.