University of Bahrain
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Influential Observations and Cutoffs of Different Influence Measures in Multiple Linear Regression

Show simple item record Kr.Das, Mintu Gogoi, Bipin 2018-08-01T05:34:58Z 2018-08-01T05:34:58Z 2015
dc.identifier.issn 2384-4795
dc.description.abstract The analysis of data for outliers is a part of model building and data summarizing for model testing, parameter estimation, prediction and peculiarity investigations. Any influential point can disproportionately pull the ordinary least squares line and distort the predictions. Thus the detection of outlying observations is very essential in the course of model building in various disciplines, such as, medical research, economics, sociology, computer science, etc. A point is an influential one if it causes dramatic change in the model after its deletion. Each of the available test statistics has different cutoff values that indicate the amount of outlyingness. Sometimes only one statistic is sufficient to provide the information about influential points but often it is necessary to examine the cutoff of more than one influence measure. The reason behind is that all the cutoff values are either a function of the sample size or number of predictors or both. Also validity of the cutoff value is subjected to some additional conditions. In this paper we try to critically examine those conditions with the help of simulation study. We shall use a few combinations of (n,k) , where n is the sample size and k is the no. of outliers for assessing the performances. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-ShareAlike 4.0 International *
dc.rights.uri *
dc.subject Influential observations
dc.subject Cooks distance
dc.subject DFFITS
dc.subject COVRATIO and Leverage
dc.title Influential Observations and Cutoffs of Different Influence Measures in Multiple Linear Regression en_US
dc.type Article en_US
dc.volume 02
dc.issue 02
dc.source.title International Journal of Computational and Theoretical Statistics
dc.abbreviatedsourcetitle IJCTS

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