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An Advanced Count Data Model with Applications in Genetics |
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PP: 113-121 |
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doi:10.18576/amisl/060303
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Author(s) |
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Zahoor Ahmad,
Adil Rahsid,
T. R. Jan,
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Abstract |
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| The present paper introduces an advanced count model which is obtained by compounding generalized negative binomial distribution with Kumaraswamy distribution. The proposed model has several properties such as it can be nested to different existing compound distributions on specific parameter setting. Similarity of the proposed model with existing compound distribution has been shown by means of reparameterization. The properties of the new model are discussed and explicit expressions are derived for the factorial moments. Further method of moments and maximum likelihood estimation is used to evaluate the moments. The potentiality of the proposed model has been tested by chi-square goodness of fit test by modeling the real world count data sets from genetics.
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