Permutation-based multivariate regression analysis: The case for least sum of absolute deviations regression

被引：6

作者：

Mielke, PW

Berry, KJ

机构：

[1] COLORADO STATE UNIV,DEPT STAT,FT COLLINS,CO 80523

[2] COLORADO STATE UNIV,DEPT SOCIOL,FT COLLINS,CO 80523

来源：

ANNALS OF OPERATIONS RESEARCH | 1997年 / 74卷 / 0期

关键词：

agreement; distribution-free; linear regression; nonlinear regression; permutation tests; statistical inference;

D O I：

10.1023/A:1018926522359

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

Linear and nonlinear multivariate least sum of absolute deviations regression models are profiled and evaluated. A chance-corrected measure of agreement between observed and predicted values is presented, a technique for establishing empirically-derived quantile limits for predicted values is introduced, and a permutation-based inference procedure for the measure of agreement is described.

引用

页码：259 / 268

页数：10

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