Hacettepe Journal of Mathematics and Statistics · 2014 · 20 citations · 11 references
BusinessDecision SciencesStatistical ModelingStatisticsTime Series AnalysisData AnalysisInferential StatisticsInfluence AnalysisRegressionStatistical AnalysisCook's DistanceCritical PointsDensity Probability Distribution FunctionExact Distribution TheoryLinear RegressionMultiple RegressionProbability Density Function EstimationProbability Density Function Modeling
Dr. G.S. David Sam Jayakumar, Assistant Professor, Jamal Institute of Management, Tiruchirappalli 620 020, India, E-mail:samjaya77@gmail.com A.Sulthan, Research scholar, Jamal Institute of Management, Tiruchirappalli 620 020, India, E-mail: Sulthan90@gmail.com Abstract: This paper proposed the exact distribution of Cook’s distance used to evaluate the influential observations in multiple linear regression analysis. The authors adopted the relationship proposed by Weisberg (1980), Belsey et al. (1980) and showed the derived density function of the cook’s distance in terms of the series expression form. Moreover, the first two moments of the distribution are derived and the authors computed the critical points of Cook’s distance at 5 % and 1 % significance level for different sample sizes based on no.of predictors. Finally, the numerical example shows the identification of the influential observations and the results extracted from the proposed approach is more scientific, systematic and it’s exactness outperforms the traditional rule of thumb approach.
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Richard J. Beckman, Sanford Weisberg · Technometrics · 1987 · 2.9K citations
Residuals and Influence in Regression
Robert F. Ling, R. Dennis Cook, Sanford Weisberg · Technometrics · 1984 · 2.7K citations · Full text
Detection of Influential Observation in Linear Regression
R. Dennis Cook · Technometrics · 2000 · 2.3K citations
Kenneth A. Bollen, Robert W. Jackman · Sociological Methods & Research · 1985 · 645 citations