Detection of Influential Observation in Linear Regression
TechnometricsPublished 1 February 2000
R. Dennis Cook
Citations2,304
SJR quartileQ1
SJR score1.41
SNIP1.93
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
A new measure based on confidence ellipsoids is developed for judging the contribution of each data point to the determination of the least squares estimate of the parameter vector in full rank linear regression models. It is shown that the measure combines information from the studentized residuals and the variances of the residuals and predicted values. Two examples are presented.
Keywords
MathematicsDecision Sciences
TechnometricsApplied Regression Analysis
18,042 Citations2005
This tutorial discusses simple and multiple linear regression, diagnostics, model selection, models with categorical variables, and nonlinear models; logistic regression.
Journal of the American Statistical AssociationAn Appraisal of Least Squares Programs for the Electronic Computer from the Point of View of the User
360 Citations1967James W. Longley
If the full potential of the electronic computer is to be achieved, an understanding of the basic arithmetic operations and their effect on the a...
TechnometricsTables for An Approximate Test for Outliers in Linear Models
241 Citations1975Richard E. Lund
BiometrikaThe effect of errors in the independent variables in linear regression
76 Citations1975Benjamin Davies, B. MUTTON
Journal of the American Statistical AssociationThe Distribution of an Arbitrary Studentized Residual and the Effects of Updating in Multiple Regression
55 Citations1974Richard J. Beckman, H.J. Trussell
