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A random variable X is strictly stable if a sum of independent copies of X has the same distribution as X up to scaling, and is stable (in the broad sense) if the sum has the same distribution as X up to both scaling and shifting. Steutel…

Probability · Mathematics 2025-09-25 Matthew Aldridge

We characterize the subexponential densities on $(0,\infty)$ for compound Poisson distributions on $[0,\infty)$ with absolutely continuous L\'evy measures. As a corollary, we show that the class of all subexponential probability density…

Probability · Mathematics 2020-01-31 Takaaki Shimura , Toshiro Watanabe

We prove that weakly continuous solutions to martingale problems admit a canonical regular conditional probability distribution. This allows for the construction of time consistent convex dynamic procedures in a non dominated setting.…

Probability · Mathematics 2012-10-09 Jocelyne Bion-Nadal

In probability theory, there is a tendency to treat one random variable with a given distribution as being just as good as any other. By and large this is fine because probability is (mostly) concerned with distributional properties of…

Probability · Mathematics 2013-01-31 Douglas Rizzolo

The fractional Poisson process (FPP) is a counting process with independent and identically distributed inter-event times following the Mittag-Leffler distribution. This process is very useful in several fields of applied and theoretical…

Probability · Mathematics 2015-05-27 Mauro Politi , Taisei Kaizoji , Enrico Scalas

On the basis of the Vlasov chain of equations, a new infinite dispersion chain of equations is obtained for the distribution functions of mixed higher order kinematical values. In contrast to the Vlasov chain, the dispersion chain contains…

Mathematical Physics · Physics 2022-01-26 E. E. Perepelkin , B. I. Sadovnikov , N. G. Inozemtseva , I. I. Aleksandrov

We derive some estimates for the integral modulus of continuity of probability densities of infinitely divisible distributions. The paper is splitted into two parts. The first part deals with general infinitely divisible distributions. The…

Probability · Mathematics 2018-05-07 David Berger

We characterize the second order subexponentiality of an infinitely divisible distribution on the real line under an exponential moment assumption. We investigate the asymptotic behaviour of the difference between the tails of an infinitely…

Probability · Mathematics 2020-01-30 Toshiro Watanabe

A characterization of the unbounded stochastic generators of quantum completely positive flows is given. This suggests the general form of quantum stochastic adapted evolutions with respect to the Wiener (diffusion), Poisson (jumps), or…

Mathematical Physics · Physics 2009-11-11 V. P. Belavkin

We introduce a class of central symmetric infinitely divisible probability measures on compact Lie groups by lifting the characteristic exponent from the real line via the Casimir operator. The class includes Gauss, Laplace and stable-type…

Probability · Mathematics 2012-02-14 David Applebaum

We formulate necessary and sufficient conditions for an arbitrary discrete probability distribution to factor according to an undirected graphical model, or a log-linear model, or other more general exponential models. This result…

Artificial Intelligence · Computer Science 2013-01-07 Dan Geiger , Christopher Meek , Bernd Sturmfels

The two-parameter Poisson-Dirichlet distribution is the law of a sequence of decreasing nonnegative random variables with total sum one. It can be constructed from stable and Gamma subordinators with the two-parameters, $\alpha$ and…

Probability · Mathematics 2009-06-15 Shui Feng , Fuqing Gao

It will be recalled that the classical bivariate normal distributions have normal marginals and normal conditionals. It is natural to ask whether a similar phenomenon can be encountered involving Poisson marginals and conditionals.…

Methodology · Statistics 2020-09-04 Barry C. Arnold , B. G. Manjunath

The Poisson distribution is the default choice of likelihood for probabilistic models of count data. However, due to the equidispersion contraint of the Poisson, such models may have predictive uncertainty that is artificially inflated.…

Methodology · Statistics 2025-07-15 Jimmy Lederman , Aaron Schein

The concept of a L\'evy subordinator is generalized to a family of non-decreasing stochastic processes, which are parameterized in terms of two Bernstein functions. Whereas the independent increments property is only maintained in the…

Probability · Mathematics 2019-09-10 Jan-Frederik Mai , Matthias Scherer

We provide the increasing eigenfunctions associated to spectrally negative self-similar Feller semigroups, which have been introduced by Lamperti. These eigenfunctions are expressed in terms of a new family of power series which includes,…

Probability · Mathematics 2009-11-09 Pierre Patie

A random dense countable set is characterized (in distribution) by independence and stationarity. Two examples are `Brownian local minima' and `unordered infinite sample'. They are identically distributed; the former ad hoc proof of this…

Probability · Mathematics 2007-05-23 Boris Tsirelson

A new discrete distribution has been proposed as a discrete analogue of the two sided power distribution [Van Drop, J. R. and Kotz, S. (2002a). A novel extension of the triangular distribution and its parameter estimation, Journal of the…

Statistics Theory · Mathematics 2015-01-27 Subrata Chakraborty , Dhrubajyoti Chakravarty

The paper provides a simpler method for proving a delicate inequality that was used by Achlioptis and Naor to establish asymptotic concentration for chromatic numbers of Erdos-Renyi random graphs. The simplifications come from two new…

Discrete Mathematics · Computer Science 2011-07-20 John Hartigan , David Pollard , Sekhar Tatikonda

This paper gives a complete characterization of infinitely divisible semimartingales, i.e., semimartingales whose finite dimensional distributions are infinitely divisible. An explicit and essentially unique decomposition of such…

Probability · Mathematics 2014-05-02 Andreas Basse-O'Connor , Jan Rosinski