Results 21 to 30 of about 1,035 (153)

A probablistic proof of the series representation of the MacDonald function with applications

International Journal of Mathematics and Mathematical Sciences, Volume 21, Issue 3, Page 463-466, 1998., 1993
A series representation of the Macdonald function is obtained using the properties of a probability density function and its moment generating function. Some applications of the result are discussed and an open problem is posed.
M. Aslam Chaudhry, Munir Ahmad
wiley   +1 more source

Modelling with star-shaped distributions

Dependence Modeling, 2020
We prove and describe in great detail a general method for constructing a wide range of multivariate probability density functions. We introduce probabilistic models for a large variety of clouds of multivariate data points.
Liebscher Eckhard, Richter Wolf-Dieter
doaj   +1 more source

On convergence of associative copulas and related results

Dependence Modeling, 2021
Triggered by a recent article establishing the surprising result that within the class of bivariate Archimedean copulas 𝒞ar different notions of convergence - standard uniform convergence, convergence with respect to the metric D1, and so-called weak ...
Kasper Thimo M., Fuchs Sebastian, Trutschnig Wolfgang   +2 more
doaj   +1 more source

On revelation transforms that characterize probability distributions

International Journal of Stochastic Analysis, Volume 6, Issue 4, Page 345-357, 1993., 1993
A characterization of exponential, geometric and of distributions with almost‐lack‐of‐memory property, based on the “revelation transform of probability distributions” and “relevation of random variables” is discussed. Known characterizations of the exponential distribution on the base of relevation transforms given by Grosswald et al. [4], and Lau and
S. Chukova, B. Dimitrov, J.-P. Dion
wiley   +1 more source

New results on perturbation-based copulas

Dependence Modeling, 2021
A prominent example of a perturbation of the bivariate product copula (which characterizes stochastic independence) is the parametric family of Eyraud-Farlie-Gumbel-Morgenstern copulas which allows small dependencies to be modeled.
Saminger-Platz Susanne, Kolesárová Anna, Šeliga Adam, Mesiar Radko, Klement Erich Peter   +4 more
doaj   +1 more source

Bounds for distribution functions of sums of squares and radial errors

International Journal of Mathematics and Mathematical Sciences, Volume 14, Issue 3, Page 561-569, 1991., 1991
Bounds are found for the distribution function of the sum of squares X2 + Y2 where X and Y are arbitrary continuous random variables. The techniques employed, which utilize copulas and their properties, show that the bounds are pointwise best‐possible when X and Y are symmetric about 0 and yield expressions which can be evaluated explicitly when X and ...
Roger B. Nelsen, Berthold Schweizer
wiley   +1 more source

Diagonal sections of copulas, multivariate conditional hazard rates and distributions of order statistics for minimally stable lifetimes

Dependence Modeling, 2021
As a motivating problem, we aim to study some special aspects of the marginal distributions of the order statistics for exchangeable and (more generally) for minimally stable non-negative random variables T1, ..., Tr. In any case, we assume that T1, ...,
Foschi Rachele, Nappo Giovanna, Spizzichino Fabio L.   +2 more
doaj   +1 more source

Stochastic orderings induced by star‐shaped functions

International Journal of Mathematics and Mathematical Sciences, Volume 14, Issue 4, Page 639-664, 1991., 1991
The non‐decreasing functions whicl are star‐shaped and supported above at each point of a non‐empty closed proper subset of the real line induce an ordering, on the class of distribution functions with finite first moments, that is strictly weaker than first degree stochastic dominance and strictly stronger than second degree stochastic dominance ...
Henry A. Krieger
wiley   +1 more source

Bayesian Inference for SIR Epidemic Model with dependent parameters

Moroccan Journal of Pure and Applied Analysis, 2022
This paper is concerned with the Bayesian inference for the dependent parameters of stochastic SIR epidemic model in a closed population. The estimation framework involves the introduction of m − 1 latent data between every pair of observations. Kibble’s
Qaffou Abdelaziz, Maroufy Hamid El, Zbair Mokhtar   +2 more
doaj   +1 more source

Correction on Moments of minors of Wishart matrices

, 2012
Correction on Moments of minors of Wishart matrices by M. Drton and A. Goia (Ann. Statist. 36 (2008) 2261-2283), arXiv:math/0604488Comment: Published in at http://dx.doi.org/10.1214/12-AOS988 the Annals of Statistics (http://www.imstat.org/aos/) by the
Drton, Mathias, Goia, Aldo
core   +1 more source