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.
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页码：259 / 268
页数：10
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