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) |
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Pages (from-to) | 91-101 |
Number of pages | 11 |
Journal | JOURNAL OF MULTIVARIATE ANALYSIS |
Volume | 100 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2009 |
Externally published | Yes |
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