A MATRIX VARIATE GENERALIZATION OF THE POWER EXPONENTIAL FAMILY OF DISTRIBUTIONS

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Model-Based Clustering (2016, unknown): “Dang et al. (2015) use the parametrization of the MPE distribution given by Gómez, Gómez-Viilegas, and Marin (1998), so that the component density for the mixture of MPEs is given by f(x | μg,Σg, βg) = k|Σg|−1/2 exp { −1 2 [ (x− μg)′Σ−1g (x− μg) ]βg} , (11) where k = pΓ (p 2 )[ πp/2Γ ( 1 +…”
Adaptive Multi-Task Lasso: with Application to eQTL Detection (2010, methodology): “We used 141 modules given by Lee et al. [3] as groups of gene traits, and extracted unique 1,260 SNPs from 2,956 SNPs for our analysis.”
Automated and semi‐automated cell tracking: addressing portability challenges (2011, background): “Gomez et al. (1998) introduce the multivariate power exponential distribution as a generalization of the normal distribution.”
A survey on continuous elliptical vector distributions (2003, background): “As an intermediate family between the normal and the elliptical ones there is the power exponential family (see [5] and [9]), which corresponds to g(t) = exp {− 12 t } for β ∈ (0,∞).”
An alternative multivariate skew Laplace distribution: properties and estimation (2010, background): “scatter matrix (e.g., see Fang et al. 1990; Lange and Sinsheimer 1993; Gomez et al. 1998; Ernst 1998; Nadarajah 2003).”