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...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Leiva, V., Sanhueza, A., Kelmansky, D.M., Martínez, E.J.
Formato: JOUR
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: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 todo:paper_01679473_v53_n5_p1613_Leiva
record_format dspace
spelling todo:paper_01679473_v53_n5_p1613_Leiva2023-10-03T15:05:36Z On the glog-normal distribution and its application to the gene expression problem Leiva, V. Sanhueza, A. Kelmansky, D.M. Martínez, E.J. 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. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar 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
Leiva, V.
Sanhueza, A.
Kelmansky, D.M.
Martínez, E.J.
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.
format JOUR
author Leiva, V.
Sanhueza, A.
Kelmansky, D.M.
Martínez, E.J.
author_facet Leiva, V.
Sanhueza, A.
Kelmansky, D.M.
Martínez, E.J.
author_sort Leiva, V.
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
url http://hdl.handle.net/20.500.12110/paper_01679473_v53_n5_p1613_Leiva
work_keys_str_mv AT leivav ontheglognormaldistributionanditsapplicationtothegeneexpressionproblem
AT sanhuezaa ontheglognormaldistributionanditsapplicationtothegeneexpressionproblem
AT kelmanskydm ontheglognormaldistributionanditsapplicationtothegeneexpressionproblem
AT martinezej ontheglognormaldistributionanditsapplicationtothegeneexpressionproblem
_version_ 1807315804298936320

Ejemplares similares