On the determination of the number of outliers in Geometric sample
by Mathachan Pathiyil and E.S Jeevanand.
Any one who has carried out experiments and collected data on a number of
occasions must have been confronted with outliers, discordant or spurious observations.
It is tempting to remove extreme values from a data set because they will incorrectly alter
the calculated statistics from the reality. The problem is quite an old one and the main
aim is to introduce some degree of objectivity into the rejection of outlying observations.
It seems that the problem of identification of the outliers in the geometric set up is not
much discussed in the available literature and the present work is an attempt to fill this
gap. In this paper we suggest procedures for the determination of the number of outliers
present in a sample taken from geometric distribution when the data is in the form of a
frequency distribution. We also compare our procedure with identification of outlier
procedure based on the posterior density proposed by Kale and Kale and the method of
least square by Wu.
Geometric distribution, Outliers, Survival function, Bayes method
Mathachan Pathiyil, email@example.com
E.S. Jeevanand, firstname.lastname@example.org
McKean, Joseph W., email@example.com
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