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Multivariate Skew-Normal Generalized Hyperbolic distribution and its properties
(Elsevier IncSan DiegoEUA, 2014)
Hypotheses tests on the skewness parameter in a multivariate generalized hyperbolic distribution
(BRAZILIAN STATISTICAL ASSOCIATION, 2021)
The class of generalized hyperbolic (GH) distributions is generated by a mean-variance mixture of a multivariate Gaussian with a generalized inverse Gaussian (GIG) distribution. This rich family of GH distributions includes ...
Subdifferential characterization of probability functions under Gaussian distribution
(Springer Verlag, 2019)
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society. Probability functions figure prominently in optimization problems of engineering. They may be nonsmooth even if all input ...
Elicitation of multivariate prior distributions: A nonparametric Bayesian approach
(Elsevier B.V., 2010-07-01)
In the context of Bayesian statistical analysis, elicitation is the process of formulating a prior density f(.) about one or more uncertain quantities to represent a person's knowledge and beliefs. Several different methods ...
Elicitation of multivariate prior distributions: A nonparametric Bayesian approach
(Elsevier B.V., 2010-07-01)
In the context of Bayesian statistical analysis, elicitation is the process of formulating a prior density f(.) about one or more uncertain quantities to represent a person's knowledge and beliefs. Several different methods ...
Elicitation of multivariate prior distributions: A nonparametric Bayesian approach
(Elsevier B.V., 2014)
Substitution random fields with Gaussian and gamma distributions: Theory and application to a pollution data set
(SPRINGER HEIDELBERG, 2008-01)
This paper presents random field models with Gaussian or gamma univariate distributions and isofactorial bivariate distributions, constructed by composing two independent random fields: a directing function with stationary ...
A visual EEG epilepsy detection method based on a wavelet statistical representation and the Kullback-Leibler divergence
(Springer Verlag, 2017-04)
This paper presents a statistical signal processing method for the characterization of EEG of patients suffering from epilepsy. A statistical model is proposed for the signals and the Kullback-Leibler divergence is used ...
Seleção de covariância para o modelo grafo gaussiano via reversible jump
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2023-02-24)
The purpose of the Graphical Gaussian model is to find the covariance structure that represents the relationship between random variables, whose joint distribution is a multivariate normal. This is a tool used to modeling ...
Particulate matter pollution from a small coke-burning factory: soil magnetic screening and its relation with a simple atmospheric dispersion model
(Springer, 2016-04)
Coal combustion processes lead to release of gases and particulate matter (PM) into the atmosphere that are often harmful to human health. These airborne pollutants seem to be dispersed and deposited in soils mainly according ...