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Non-Gaussian Price Dynamics and Implications for Option Pricing
(2012)
It is well known that the probability distribution of stock returns is non-Gaussian. The tails of the distribution are too “fat,” meaning that extreme price movements, such as stock market crashes, occur more often than ...
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)
Use of the q-Gaussian mutation in evolutionary algorithms
(SPRINGER, 2011)
This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real ...
Degradation modeling for reliability analysis with time-dependent structure based on the inverse gaussian distribution
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2017-04-07)
Conventional reliability analysis techniques are focused on the occurrence of failures over
time. However, in certain situations where the occurrence of failures is tiny or almost null, the
estimation of the quantities ...
On the determination of epsilon during discriminative GMM training
(2010-12-01)
Discriminative training of Gaussian Mixture Models (GMMs) for speech or speaker recognition purposes is usually based on the gradient descent method, in which the iteration step-size, ε, uses to be defined experimentally. ...
The kappa-mu distribution and the eta-mu distribution
(Ieee-inst Electrical Electronics Engineers IncPiscatawayEUA, 2007)
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 ...