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On the glog-normal distribution and its application to the gene expression problem

Author

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  • Leiva, Vctor
  • Sanhueza, Antonio
  • Kelmansky, Diana M.
  • Martnez, Elena J.

Abstract

In this article, we characterized the glog-normal distribution and present a comprehensive treatment of the properties of this model. Specifically, we present the probability density function as well as a graphical analysis of this density, the cumulative distribution function and the moments for this statistical distribution. Additionally, by using likelihood methods, we estimate the parameters, carry out asymptotic inference and discuss influence diagnostics of this model. Finally, we show the usefulness of the glog-normal distribution for modeling gene expression microarray intensity data by means of a real numerical example.

Suggested Citation

  • Leiva, Vctor & Sanhueza, Antonio & Kelmansky, Diana M. & Martnez, Elena J., 2009. "On the glog-normal distribution and its application to the gene expression problem," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1613-1621, March.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:5:p:1613-1621
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    References listed on IDEAS

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    1. Huber Wolfgang & von Heydebreck Anja & Sueltmann Holger & Poustka Annemarie & Vingron Martin, 2003. "Parameter estimation for the calibration and variance stabilization of microarray data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 2(1), pages 1-24, April.
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    Cited by:

    1. García, V.J. & Gómez-Déniz, E. & Vázquez-Polo, F.J., 2010. "A new skew generalization of the normal distribution: Properties and applications," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 2021-2034, August.

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