Open AccessUSING ASYMMETRIC DISTRIBUTIONS FOR MODELING GENE EXPRESSION DATA
Author(s) -
Walkiria Maria de Oliveira Macerau,
Luís Aparecido Milan
Publication year - 2021
Publication title -
revista de matemática e estatística
Language(s) - English
Resource type - Journals
eISSN - 1980-4245
pISSN - 0102-0811
DOI - 10.28951/rbb.v39i2.466
Subject(s) - skew , data set , expression (computer science) , set (abstract data type) , skew normal distribution , laplace transform , mathematics , alpha (finance) , computer science , statistics , mathematical analysis , telecommunications , programming language , construct validity , psychometrics
We present a short review of the asymmetric distributions alpha-stable, skew normal, skew Student’s t and skew Laplace. We compare the performance for these distributions, in general, are used to model asymmetric data, using AIC and BIC. These criterias were able to selecting the best model for each data set. We also apply these models to gene expression data and we verify these distributions are qualified to model these observations.