ANALYSIS OF CONSTRAINED ROBUST REGRESSION ESTIMATORS.

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Multicollinearity and nonnormal errors are problems often encountered in the application of linear regression. Estimators are proposed for dealing with the simultaneous occurrence of both multicollinearity and nonnormality. These estimators are developed by combining biased estimation techniques with certain robust criteria. An iteratively reweighted least-squares procedure is used to compute the estimates. The performance of the combined estimators is studied empirically through Monte Carlo experiments structured according to factorial designs. Some guidelines for the use of these combined estimators are given.

Original languageEnglish (US)
Pages (from-to)283-296
Number of pages14
JournalNaval Research Logistics Quarterly
Volume31
Issue number2
StatePublished - Jun 1984
Externally publishedYes

Fingerprint

Robust Regression
Robust Estimators
Regression Estimator
Linear regression
Estimator
Multicollinearity
Experiments
Biased Estimation
Iteratively Reweighted Least Squares
Non-normality
Factorial Design
Monte Carlo Experiment
Robust regression
Estimate

ASJC Scopus subject areas

  • Engineering(all)

Cite this

ANALYSIS OF CONSTRAINED ROBUST REGRESSION ESTIMATORS. / Askin, Ronald; Montgomery, Douglas.

In: Naval Research Logistics Quarterly, Vol. 31, No. 2, 06.1984, p. 283-296.

Research output: Contribution to journalArticle

@article{a1231d8907c94183a69b2ef61a93c21c,
title = "ANALYSIS OF CONSTRAINED ROBUST REGRESSION ESTIMATORS.",
abstract = "Multicollinearity and nonnormal errors are problems often encountered in the application of linear regression. Estimators are proposed for dealing with the simultaneous occurrence of both multicollinearity and nonnormality. These estimators are developed by combining biased estimation techniques with certain robust criteria. An iteratively reweighted least-squares procedure is used to compute the estimates. The performance of the combined estimators is studied empirically through Monte Carlo experiments structured according to factorial designs. Some guidelines for the use of these combined estimators are given.",
author = "Ronald Askin and Douglas Montgomery",
year = "1984",
month = "6",
language = "English (US)",
volume = "31",
pages = "283--296",
journal = "Naval Research Logistics",
issn = "0894-069X",
publisher = "John Wiley and Sons Inc.",
number = "2",

}

TY - JOUR

T1 - ANALYSIS OF CONSTRAINED ROBUST REGRESSION ESTIMATORS.

AU - Askin, Ronald

AU - Montgomery, Douglas

PY - 1984/6

Y1 - 1984/6

N2 - Multicollinearity and nonnormal errors are problems often encountered in the application of linear regression. Estimators are proposed for dealing with the simultaneous occurrence of both multicollinearity and nonnormality. These estimators are developed by combining biased estimation techniques with certain robust criteria. An iteratively reweighted least-squares procedure is used to compute the estimates. The performance of the combined estimators is studied empirically through Monte Carlo experiments structured according to factorial designs. Some guidelines for the use of these combined estimators are given.

AB - Multicollinearity and nonnormal errors are problems often encountered in the application of linear regression. Estimators are proposed for dealing with the simultaneous occurrence of both multicollinearity and nonnormality. These estimators are developed by combining biased estimation techniques with certain robust criteria. An iteratively reweighted least-squares procedure is used to compute the estimates. The performance of the combined estimators is studied empirically through Monte Carlo experiments structured according to factorial designs. Some guidelines for the use of these combined estimators are given.

UR - http://www.scopus.com/inward/record.url?scp=0021444915&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0021444915&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0021444915

VL - 31

SP - 283

EP - 296

JO - Naval Research Logistics

JF - Naval Research Logistics

SN - 0894-069X

IS - 2

ER -