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The multivariate skew-slash t and skew-slash Cauchy distributions
Model Assisted Statistics and Applications, 2012The slash distributions are flexible distributions that can take skewness and heavy tails into account. In this article we define skewed versions of multivariate slash t distribution and multivariate slash Cauchy distribution. These distributions belong to the multivariate skew-slash elliptical family.
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Multivariate skew-normal distribution for modelling skewed spatial data
Spatial and Spatio-temporal EpidemiologyMultivariate spatial data are commonly modelled using the shared spatial component and multivariate intrinsic conditional autoregressive (MICAR) models where the spatial random variables are assumed to be normally distributed. However, the normality assumption may not be always right as the spatially structured component may show non-normal ...
Kassahun Abere Ayalew +2 more
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On a measure of multivariate skewness and a test for multivariate normality
Annals of the Institute of Statistical Mathematics, 1982We consider an extension of Pearson measure of skewness to a multivariate case and apply the proposed measure to a test of multivariate normality.
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Accelerating the Multivariate SKEW T Parameter Estimation
2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019This paper considers an acceleration scheme for the multivariate skew $t$ (MST) parameter estimation. MST is a heavy-tailed distribution allowing also for skewness. The distribution is very convenient for many real-life applications where there data is heavy-tailed, there may be outliers, and data may be skewed. One example is financial data.
Rui Zhou 0016, Daniel P. Palomar
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Regularized skewness parameter estimation for multivariate skew normal and skew t distributions
2019<p>The skewed normal (SN) distribution introduced by Azzalini has opened a new era for analyzing skewed data. The idea behind it is that it incorporates a new parameter regulating shape and skewness on the symmetric Gaussian distribution. This idea was soon extended to other symmetric distributions such as the Student's t distribution, resulting ...
Sheng Wang +5 more
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Flexible Modelling via Multivariate Skew Distributions
2019Mixtures of skew component distributions are being applied widely to model and partition data into clusters that exhibit non-normal features such as asymmetry and tails heavier than the normal. The number of contributions on skew distributions are now so many that it is beyond the scope of this paper to include them all here.
Geoffrey J. McLachlan, Sharon X. Lee
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The Skew-normal Distribution and Related Multivariate Families*
Scandinavian Journal of Statistics, 2005If \(f_0\) is a \(d\)-dimensional density with \(f_0(x)=f_0(-x)\), \(G\) is a one-dimensional CDF with symmetric about 0 PDF and \(w: R^d\to R\) is any function with \(w(-x)=-w(x)\), then \(f(z)=2f_0(z)G(w(z))\) is a density function on \(R^d\). With \(f_0\sim N(0,\Omega)\), \(G\sim N(0,1)\), and a linear function \(w\) one obtains \(f\) being a skew ...
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Multivariate skewness and kurtosis
Journal of the Korean Data And Information Science Sociaty, 2018Chong Sun Hong, Jae Hyun Sung
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The skewness of oil price returns and equity premium predictability
Energy Economics, 2021Zhifeng Dai, Jie Kang, Fenghua Wen
exaly