Shape mixtures of multivariate skew-normal distributions

Reinaldo B. Arellano-Valle; Marc G. Genton; Rosangela H. Loschi

doi:10.1016/j.jmva.2008.03.009

Shape mixtures of multivariate skew-normal distributions

Reinaldo B. Arellano-Valle, Marc G. Genton^*, Rosangela H. Loschi

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

Abstract

Classes of shape mixtures of independent and dependent multivariate skew-normal distributions are considered and some of their main properties are studied. If interpreted from a Bayesian point of view, the results obtained in this paper bring tractability to the problem of inference for the shape parameter, that is, the posterior distribution can be written in analytic form. Robust inference for location and scale parameters is also obtained under particular conditions.

Original language	English (US)
Pages (from-to)	91-101
Number of pages	11
Journal	JOURNAL OF MULTIVARIATE ANALYSIS
Volume	100
Issue number	1
DOIs	https://doi.org/10.1016/j.jmva.2008.03.009
State	Published - Jan 2009
Externally published	Yes

Bibliographical note

Funding Information:
The authors thank two referees whose comments and suggestions have contributed to the improvement of the paper. The research of R.B. Arellano-Valle was supported in part by FONDECYT (Chile), grants 1040865, 7060133 and 7070137. The work of M.G. Genton was partially supported by NSF grant DMS-0504896 and by a grant from the Swiss National Science Foundation. R.H. Loschi acknowledges CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) of the Ministry for Science and Technology of Brazil, grants 3004505/2006-4, 472066/2004-8 and 472877/2006-2, for a partial allowance to her research.

Keywords

62E15
62H05
Bayes
Conjugacy
Regression model
Robustness
Shape parameter
Skew-normal distribution
Skewness

ASJC Scopus subject areas

Statistics and Probability
Numerical Analysis
Statistics, Probability and Uncertainty

Access to Document

10.1016/j.jmva.2008.03.009

Cite this

@article{6870bb776a2247e8a26632f65a5a2b79,

title = "Shape mixtures of multivariate skew-normal distributions",

abstract = "Classes of shape mixtures of independent and dependent multivariate skew-normal distributions are considered and some of their main properties are studied. If interpreted from a Bayesian point of view, the results obtained in this paper bring tractability to the problem of inference for the shape parameter, that is, the posterior distribution can be written in analytic form. Robust inference for location and scale parameters is also obtained under particular conditions.",

keywords = "62E15, 62H05, Bayes, Conjugacy, Regression model, Robustness, Shape parameter, Skew-normal distribution, Skewness",

author = "Arellano-Valle, {Reinaldo B.} and Genton, {Marc G.} and Loschi, {Rosangela H.}",

note = "Funding Information: The authors thank two referees whose comments and suggestions have contributed to the improvement of the paper. The research of R.B. Arellano-Valle was supported in part by FONDECYT (Chile), grants 1040865, 7060133 and 7070137. The work of M.G. Genton was partially supported by NSF grant DMS-0504896 and by a grant from the Swiss National Science Foundation. R.H. Loschi acknowledges CNPq (Conselho Nacional de Desenvolvimento Cient{\'i}fico e Tecnol{\'o}gico) of the Ministry for Science and Technology of Brazil, grants 3004505/2006-4, 472066/2004-8 and 472877/2006-2, for a partial allowance to her research.",

year = "2009",

month = jan,

doi = "10.1016/j.jmva.2008.03.009",

language = "English (US)",

volume = "100",

pages = "91--101",

journal = "JOURNAL OF MULTIVARIATE ANALYSIS",

issn = "0047-259X",

publisher = "Academic Press Inc.",

number = "1",

}

TY - JOUR

T1 - Shape mixtures of multivariate skew-normal distributions

AU - Arellano-Valle, Reinaldo B.

AU - Genton, Marc G.

AU - Loschi, Rosangela H.

N1 - Funding Information: The authors thank two referees whose comments and suggestions have contributed to the improvement of the paper. The research of R.B. Arellano-Valle was supported in part by FONDECYT (Chile), grants 1040865, 7060133 and 7070137. The work of M.G. Genton was partially supported by NSF grant DMS-0504896 and by a grant from the Swiss National Science Foundation. R.H. Loschi acknowledges CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) of the Ministry for Science and Technology of Brazil, grants 3004505/2006-4, 472066/2004-8 and 472877/2006-2, for a partial allowance to her research.

PY - 2009/1

Y1 - 2009/1

N2 - Classes of shape mixtures of independent and dependent multivariate skew-normal distributions are considered and some of their main properties are studied. If interpreted from a Bayesian point of view, the results obtained in this paper bring tractability to the problem of inference for the shape parameter, that is, the posterior distribution can be written in analytic form. Robust inference for location and scale parameters is also obtained under particular conditions.

AB - Classes of shape mixtures of independent and dependent multivariate skew-normal distributions are considered and some of their main properties are studied. If interpreted from a Bayesian point of view, the results obtained in this paper bring tractability to the problem of inference for the shape parameter, that is, the posterior distribution can be written in analytic form. Robust inference for location and scale parameters is also obtained under particular conditions.

KW - 62E15

KW - 62H05

KW - Bayes

KW - Conjugacy

KW - Regression model

KW - Robustness

KW - Shape parameter

KW - Skew-normal distribution

KW - Skewness

UR - http://www.scopus.com/inward/record.url?scp=55049099294&partnerID=8YFLogxK

U2 - 10.1016/j.jmva.2008.03.009

DO - 10.1016/j.jmva.2008.03.009

M3 - Article

AN - SCOPUS:55049099294

SN - 0047-259X

VL - 100

SP - 91

EP - 101

JO - JOURNAL OF MULTIVARIATE ANALYSIS

JF - JOURNAL OF MULTIVARIATE ANALYSIS

IS - 1

ER -

Shape mixtures of multivariate skew-normal distributions

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this