Please use this identifier to cite or link to this item:
Type: Artigo de periódico
Title: On a variance stabilizing model and its application to genomic data
Author: Vilca, F
Rodrigues-Motta, M
Leiva, V
Abstract: In this paper, we propose a model based on a class of symmetric distributions, which avoids the transformation of data, stabilizes the variance of the observations, and provides robust estimation of parameters and high flexibility for modeling different types of data. Probabilistic and statistical aspects of this new model are developed throughout the article, which include mathematical properties, estimation of parameters and inference. The obtained results are illustrated by means of real genomic data.
Subject: EM algorithm
Johnson system distributions
maximum-likelihood method
normal scale mixture distributions
Country: Inglaterra
Editor: Taylor & Francis Ltd
Citation: Journal Of Applied Statistics. Taylor & Francis Ltd, v. 40, n. 11, n. 2354, n. 2371, 2013.
Rights: fechado
Identifier DOI: 10.1080/02664763.2013.811480
Date Issue: 2013
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.