Explicit formulas for the cumulants and the vector-valued odd moments of the multivariate linearly skewed elliptical distributions
From MaRDI portal
Publication:5866050
DOI10.1080/03610926.2018.1473605OpenAlexW2901206073WikidataQ128928870 ScholiaQ128928870MaRDI QIDQ5866050
Publication date: 10 June 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2018.1473605
cumulantsskew-normal distributionmultivariate momentsskew-elliptical distributionsvector-valued moments
Cites Work
- Unnamed Item
- Unnamed Item
- A proof for the conjecture of characteristic function of the generalized skew-elliptical distributions
- A note on the fourth cumulant of a finite mixture distribution
- Canonical transformations of skew-normal variates
- Multivariate measures of skewness for the skew-normal distribution
- Generalized skew-elliptical distributions and their quadratic forms
- A generalized projection pursuit procedure and its significance level
- Skewed distributions generated by the normal kernel.
- A multivariate skew normal distribution.
- Some properties of skew-symmetric distributions
- Skewness and the linear discriminant function
- Vector-valued skewness for model-based clustering
- Tail conditional moments for elliptical and log-elliptical distributions
- Multivariate tail conditional expectation for elliptical distributions
- Statistical Applications of the Multivariate Skew Normal Distribution
- Bayesian Inference Based on Robust Priors and MML Estimators: Part I, Symmetric Location-Scale Distributions
- Multivariate skewt-distribution
- Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skewt-Distribution
- On the skew Laplace distribution
- Tail Conditional Expectations for Elliptical Distributions
- Moments of skew-normal random vectors and their quadratic forms
- A general class of multivariate skew-elliptical distributions
