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The exponentiated generalized inverse Gaussian distribution
(ELSEVIER SCIENCE BV, 2011)
The modeling and analysis of lifetime data is an important aspect of statistical work in a wide variety of scientific and technological fields. Good (1953) introduced a probability distribution which is commonly used in ...
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 ...
An r package for a general class of inverse gaussian distributions
(JOURNAL STATISTICAL SOFTWARE, 2008)
Random number generators for the generalized Birnbaum-Saunders distribution
(TAYLOR & FRANCIS LTD, 2008)
The generalized Birnbaum-Saunders distribution pertains to a class of lifetime models including both lighter and heavier tailed distributions. This model adapts well to lifetime data, even when outliers exist, and has other ...
Modelando la distribución del número de co-autores por artículoModeling the distribution of co-authorships by paper
(Instituto de Investigaciones Bibliotecológicas y de la Información, 2011)
A new family of generalized distributions
(TAYLOR & FRANCIS LTD, 2011)
Kumaraswamy [Generalized probability density-function for double-bounded random-processes, J. Hydrol. 462 (1980), pp. 79-88] introduced a distribution for double-bounded random processes with hydrological applications. For ...
An r package for a general class of inverse gaussian distributionsJOURNAL OF STATISTICAL SOFTWARE
(JOURNAL STATISTICAL SOFTWARE, 2016)
Iterative algorithms for non-conditional and conditional simulation of Gaussian random vectors
(Springer, 2020)
The conditional simulation of Gaussian random vectors is widely used in geostatistical applications to quantify uncertainty in regionalized phenomena that have been observed at finitely many sampling locations. Two iterative ...
Modeling and estimation of some non Gaussian random fieldsModeling and estimatión of some non gaussian random fields
(2018)
In this work, we propose two types of models for the analysis of regression and dependence of positive and continuous spatio-temporal data, and of continuous spatio-temporal data with possible asymmetry and/or heavy tails. ...