Add to ORKGFor the selfdecomposable distributions (random variables) we identified background driving probability distributions in their random integral representations. For log-gamma and their background driving random variables series representations are found
Cankaya et al. (2015) [1] introduced a bimodal extension of the generalized gamma distribution and s...
We use techniques in the shuffle and exterior algebras to present the partition functions for severa...
We obtain exact formulas for the cumulative distribution function of the variance-gamma distribution...
Many classical variables (statistics) are selfdecomposable. They admit the random integral represent...
In this paper, we study some aspects on random analysis on the L\'eevy stochastic processes with mar...
AbstractThree new properties are derived. The first one relates to the distribution ofUG+G′, where t...
We prove that the convolution of a selfdecomposable distribution with its background driving law is ...
Three new properties are derived. The first one relates to the distribution of UG q GX, where the th...
A process X(t) is self-similar with index H > 0 if the finite-dimensional distributions of X(at) are...
We develop a general method for computing logarithmic and log-gamma expectations of distributions. A...
Probability density function (pdf) for sum of n correlated lognormal variables is deducted as a spe...
Some distributional properties of the generalized type 1 logistic distribution are given. Based on t...
We present a class of Lévy processes for modelling financial market fluctuations: Bilateral Gamma pr...
We consider some special classes of Lévy processes with no gaussian component whose Lévy measure is ...
This thesis focuses on various aspects of non-Gaussian distributions and processes sharing scaling p...
Cankaya et al. (2015) [1] introduced a bimodal extension of the generalized gamma distribution and s...
We use techniques in the shuffle and exterior algebras to present the partition functions for severa...
We obtain exact formulas for the cumulative distribution function of the variance-gamma distribution...
Many classical variables (statistics) are selfdecomposable. They admit the random integral represent...
In this paper, we study some aspects on random analysis on the L\'eevy stochastic processes with mar...
AbstractThree new properties are derived. The first one relates to the distribution ofUG+G′, where t...
We prove that the convolution of a selfdecomposable distribution with its background driving law is ...
Three new properties are derived. The first one relates to the distribution of UG q GX, where the th...
A process X(t) is self-similar with index H > 0 if the finite-dimensional distributions of X(at) are...
We develop a general method for computing logarithmic and log-gamma expectations of distributions. A...
Probability density function (pdf) for sum of n correlated lognormal variables is deducted as a spe...
Some distributional properties of the generalized type 1 logistic distribution are given. Based on t...
We present a class of Lévy processes for modelling financial market fluctuations: Bilateral Gamma pr...
We consider some special classes of Lévy processes with no gaussian component whose Lévy measure is ...
This thesis focuses on various aspects of non-Gaussian distributions and processes sharing scaling p...
Cankaya et al. (2015) [1] introduced a bimodal extension of the generalized gamma distribution and s...
We use techniques in the shuffle and exterior algebras to present the partition functions for severa...
We obtain exact formulas for the cumulative distribution function of the variance-gamma distribution...