Title : ( Detecting Outliers in Gamma Distribution )
Authors: Mehdi Jabbari Nooghabi , Hadi Jabbari Nooghabi , P. Nasiri ,
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Abstract
Zerbet and nikulin presented the new statistic Z_k for detecting outliers in Exponential distribution. They also compared this statistic with Dixon s statistic D_k. In this paper, we extend this approach to Gamma distribution and compare the result with Dixon s statistic. The results show that the test based on statistic Z_k is more powerful than the test based on the Dixon s statistic.
Keywords
, Gamma sample, Z statistic, Dixon s statistic, Outlier, Slippage hypothesis, Test of Chauvenet, Upper outlier, Power of the test.
@article{paperid:1006267,
author = {Jabbari Nooghabi, Mehdi and Jabbari Nooghabi, Hadi and P. Nasiri},
title = {Detecting Outliers in Gamma Distribution},
journal = {Communications in Statistics - Theory and Methods},
year = {2010},
volume = {39},
number = {4},
month = {October},
issn = {0361-0926},
pages = {698--706},
numpages = {8},
keywords = {Gamma sample; Z statistic; Dixon s statistic; Outlier; Slippage hypothesis; Test of Chauvenet; Upper outlier; Power of the test.},
}
%0 Journal Article
%T Detecting Outliers in Gamma Distribution
%A Jabbari Nooghabi, Mehdi
%A Jabbari Nooghabi, Hadi
%A P. Nasiri
%J Communications in Statistics - Theory and Methods
%@ 0361-0926
%D 2010
