The mixture of factor analyzers model, which has been used successfully for the model-based clustering of high-dimensional data, is extended to generalized hyperbolic mixtures. The development of a mixture of generalized hyperbolic factor analyzers is outlined, drawing upon the relationship with the generalized inverse Gaussian distribution. An alternating expectation-conditional maximization a...

This paper addresses the Bayesian calibration of dynamic models with parametric and structural uncertainties, in particular where the uncertain parameters are unknown/poorly known spatio-temporally varying subsystem models. Independent stationary Gaussian processes with uncertain hyper-parameters describe uncertainties of the model structure and parameters while Karhunnen-Loeve expansion is ado...

In this paper we have introduced extensions yv(a, x; b) and fu(a, x; b) of the generalized Gamma functions y (a, x; b) and V(a, x\ b) considered recently by Chaudhry and Zubair. These extensions are found useful in the representations of the Laplace and tf-transforms of a class of functions. We have also defined a generalization of the inverse Gaussian distribution. The cumulative and the relia...

2014 We establish classically the probability distribution (P-distribution) for the complex amplitudes of multimodal and unimodal optical fields belonging to the class of generalized Gaussian fields recently introduced. From this result follows immediately the unique P-representation for this class of fields. However, all the generalized Gaussian fields, except the chaotic field, are not fully ...

In portfolio theory, it is well-known that the distributions of stock returns often have non-Gaussian characteristics. Therefore, we need non-symmetric distributions for modeling and accurate analysis of actuarial data. For this purpose and optimal portfolio selection, we use the Tail Mean-Variance (TMV) model, which focuses on the rare risks but high losses and usually happens in the tail of r...

Digital watermarks are usually embedded in the still images’ frequency domain. The DWT/DCT coefficients are usually modelled by the Generalized Gaussian Distribution, while the DFT coefficients are modelled by the Weibull Distribution. The idea of this paper is to use statistical properties of the host signal. The watermark is embedded through the modification of the distribution of host signal...

in this paper a new algorithm is presented for coherent radar detection of targets, when distribution of the interference (clutter and noise) is non-gaussian. the neyman-pearson criterion is used for optimal detection and several successive received samples from a radar range cell are used for detection in the same cell. on the basis of recent empirical evidences, the interference distribution ...

We introduce a mixture of generalized hyperbolic distributions as an alternative to the ubiquitous mixture of Gaussian distributions as well as their near relatives of which the mixture of multivariate t and skew-t distributions are predominant. The mathematical development of our mixture of generalized hyperbolic distributions model relies on its relationship with the generalized inverse Gauss...