Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
Bayesian Inference for Skew-Symmetric Distributions
View through CrossRef
Skew-symmetric distributions are a popular family of flexible distributions that conveniently model non-normal features such as skewness, kurtosis and multimodality. Unfortunately, their frequentist inference poses several difficulties, which may be adequately addressed by means of a Bayesian approach. This paper reviews the main prior distributions proposed for the parameters of skew-symmetric distributions, with special emphasis on the skew-normal and the skew-t distributions which are the most prominent skew-symmetric models. The paper focuses on the univariate case in the absence of covariates, but more general models are also discussed.
Title: Bayesian Inference for Skew-Symmetric Distributions
Description:
Skew-symmetric distributions are a popular family of flexible distributions that conveniently model non-normal features such as skewness, kurtosis and multimodality.
Unfortunately, their frequentist inference poses several difficulties, which may be adequately addressed by means of a Bayesian approach.
This paper reviews the main prior distributions proposed for the parameters of skew-symmetric distributions, with special emphasis on the skew-normal and the skew-t distributions which are the most prominent skew-symmetric models.
The paper focuses on the univariate case in the absence of covariates, but more general models are also discussed.
Related Results
Sample-efficient Optimization Using Neural Networks
Sample-efficient Optimization Using Neural Networks
<p>The solution to many science and engineering problems includes identifying the minimum or maximum of an unknown continuous function whose evaluation inflicts non-negligibl...
Figs S1-S9
Figs S1-S9
Fig. S1. Consensus phylogram (50 % majority rule) resulting from a Bayesian analysis of the ITS sequence alignment of sequences generated in this study and reference sequences from...
Models de distribució sobre el símplex
Models de distribució sobre el símplex
Les dades composicionals són vectors les components dels quals representen proporcions respecte d'un total, i per tant estan sotmesos a la restricció que la suma de les seves compo...
Extended Bayesian inference incorporating symmetry bias
Extended Bayesian inference incorporating symmetry bias
AbstractIn this study, we start by proposing a causal induction model that incorporates symmetry bias. This model has two parameters that control the strength of symmetry bias and ...
Incomplete Cross Splitting in the Approximation of Skew-Symmetric Matrix Exponential
Incomplete Cross Splitting in the Approximation of Skew-Symmetric Matrix Exponential
This paper proposes a new splitting method for approximating the
exponential of skew-symmetric and skew-Hermitian matrix A . Our point of
departure is the splitting methods for app...
Influences on flood frequency distributions in Irish river catchments
Influences on flood frequency distributions in Irish river catchments
Abstract. This study explores influences which result in shifts of flood frequency distributions in Irish rivers. Generalised Extreme Value (GEV) type I distributions are recommend...
Bayesian implementation of Skew-Normal distributions for experimental error in the description of pepper growth
Bayesian implementation of Skew-Normal distributions for experimental error in the description of pepper growth
The purpose of this work is to implement and compare three types of Skew-Normal distributions together with the Normal submodel for the experimental error through a Bayesian nonlin...
Evolutionary Grammatical Inference
Evolutionary Grammatical Inference
Grammatical Inference (also known as grammar induction) is the problem of learning a grammar for a language from a set of examples. In a broad sense, some data is presented to the ...