Bayesian approach to epsilon-skew-normal family

The estimation problem of epsilon-skew-normal (ESN) distribution parameters is considered within Bayesian approaches. This family of distributions contains the normal distribution, can be used for analyzing the asymmetric and near-normal data. Bayesian estimates under informative and non informative...

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Published inCommunications in statistics. Theory and methods Vol. 46; no. 15; pp. 7546 - 7561
Main Authors Maleki, M., Nematollahi, A. R.
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 03.08.2017
Taylor & Francis Ltd
Subjects
Bayes estimates
Bayesian analysis
Epsilon skew normal
Frequentist risk
Jeffreys prior
Normal distribution
Skewed distributions
Skewness
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Abstract The estimation problem of epsilon-skew-normal (ESN) distribution parameters is considered within Bayesian approaches. This family of distributions contains the normal distribution, can be used for analyzing the asymmetric and near-normal data. Bayesian estimates under informative and non informative Jeffreys prior distributions are obtained and performances of ESN family and these estimates are shown via a simulation study. A real data set is also used to illustrate the ideas.
AbstractList The estimation problem of epsilon-skew-normal (ESN) distribution parameters is considered within Bayesian approaches. This family of distributions contains the normal distribution, can be used for analyzing the asymmetric and near-normal data. Bayesian estimates under informative and non informative Jeffreys prior distributions are obtained and performances of ESN family and these estimates are shown via a simulation study. A real data set is also used to illustrate the ideas.
Author Maleki, M.
Nematollahi, A. R.
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SubjectTerms Bayes estimates
Bayesian analysis
Epsilon skew normal
Frequentist risk
Jeffreys prior
Normal distribution
Skewed distributions
Skewness
Title Bayesian approach to epsilon-skew-normal family
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