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

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 th...

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Detalles Bibliográficos
Autores principales: Kelmansky, Diana M., Martínez, Elena Julia
Publicado: 2009
Materias:
Bioactivity
Distribution functions
Gene expression
Probability density function
Probability distributions
Cumulative distribution functions
Expression problems
Gene expression microarrays
Graphical analysis
Intensity datum
Likelihood methods
Numerical examples
Probability densities
Statistical distributions
Normal distribution
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01679473_v53_n5_p1613_Leiva
http://hdl.handle.net/20.500.12110/paper_01679473_v53_n5_p1613_Leiva
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_01679473_v53_n5_p1613_Leiva
record_format dspace
spelling paper:paper_01679473_v53_n5_p1613_Leiva2023-06-08T15:17:09Z On the glog-normal distribution and its application to the gene expression problem Kelmansky, Diana M. Martínez, Elena Julia Bioactivity Distribution functions Gene expression Probability density function Probability distributions Cumulative distribution functions Expression problems Gene expression microarrays Graphical analysis Intensity datum Likelihood methods Numerical examples Probability densities Statistical distributions Normal distribution 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. © 2008 Elsevier B.V. All rights reserved. Fil:Kelmansky, D.M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Martínez, E.J. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2009 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01679473_v53_n5_p1613_Leiva http://hdl.handle.net/20.500.12110/paper_01679473_v53_n5_p1613_Leiva
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Bioactivity
Distribution functions
Gene expression
Probability density function
Probability distributions
Cumulative distribution functions
Expression problems
Gene expression microarrays
Graphical analysis
Intensity datum
Likelihood methods
Numerical examples
Probability densities
Statistical distributions
Normal distribution
spellingShingle Bioactivity
Distribution functions
Gene expression
Probability density function
Probability distributions
Cumulative distribution functions
Expression problems
Gene expression microarrays
Graphical analysis
Intensity datum
Likelihood methods
Numerical examples
Probability densities
Statistical distributions
Normal distribution
Kelmansky, Diana M.
Martínez, Elena Julia
On the glog-normal distribution and its application to the gene expression problem
topic_facet Bioactivity
Distribution functions
Gene expression
Probability density function
Probability distributions
Cumulative distribution functions
Expression problems
Gene expression microarrays
Graphical analysis
Intensity datum
Likelihood methods
Numerical examples
Probability densities
Statistical distributions
Normal distribution
description 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. © 2008 Elsevier B.V. All rights reserved.
author Kelmansky, Diana M.
Martínez, Elena Julia
author_facet Kelmansky, Diana M.
Martínez, Elena Julia
author_sort Kelmansky, Diana M.
title On the glog-normal distribution and its application to the gene expression problem
title_short On the glog-normal distribution and its application to the gene expression problem
title_full On the glog-normal distribution and its application to the gene expression problem
title_fullStr On the glog-normal distribution and its application to the gene expression problem
title_full_unstemmed On the glog-normal distribution and its application to the gene expression problem
title_sort on the glog-normal distribution and its application to the gene expression problem
publishDate 2009
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01679473_v53_n5_p1613_Leiva
http://hdl.handle.net/20.500.12110/paper_01679473_v53_n5_p1613_Leiva
work_keys_str_mv AT kelmanskydianam ontheglognormaldistributionanditsapplicationtothegeneexpressionproblem
AT martinezelenajulia ontheglognormaldistributionanditsapplicationtothegeneexpressionproblem
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