Infinitely divisible probability measures and the converse Kolmogorov inequality in Banach spaces
Infinitely divisible random probability distributions with an application to a random motion in a random environment.
Information-type divergence when the likelihood ratios are bounded
The so-called ϕ-divergence is an important characteristic describing "dissimilarity" of two probability distributions. Many traditional measures of separation used in mathematical statistics and information theory, some of which are mentioned in the note, correspond to particular choices of this divergence. An upper bound on a ϕ-divergence between two probability distributions is derived when the likelihood ratio is bounded. The usefulness of this sharp bound is illustrated by several examples of...
Integral criteria for transportation-cost inequalities.
Integrated Pearson family and orthogonality of the Rodrigues polynomials: A review including new results and an alternative classification of the Pearson system
An alternative classification of the Pearson family of probability densities is related to the orthogonality of the corresponding Rodrigues polynomials. This leads to a subset of the ordinary Pearson system, the so-called Integrated Pearson Family. Basic properties of this family are discussed and reviewed, and some new results are presented. A detailed comparison between the Integrated Pearson Family and the ordinary Pearson system is presented, including an algorithm that enables one to decide...
Interolation, Correlation Identities, and Inequalities for Infinitely Divisible Variables.
Interpolated inequalities between exponential and Gaussian, Orlicz hypercontractivity and isoperimetry.
We introduce and study a notion of Orlicz hypercontractive semigroups. We analyze their relations with general F-Sobolev inequalities, thus extending Gross hypercontractivity theory. We provide criteria for these Sobolev type inequalities and for related properties. In particular, we implement in the context of probability measures the ideas of Maz'ja's capacity theory, and present equivalent forms relating the capacity of sets to their measure. Orlicz hypercontractivity efficiently describes the...
Invariance of relative inverse function orderings under compositions of distributions
Bartoszewicz and Benduch (2009) applied an idea of Lehmann and Rojo (1992) to a new setting and used the GTTT transform to define invariance properties and distances of some stochastic orders. In this paper Lehmann and Rojo's idea is applied to the class of models which is based on distributions which are compositions of distribution functions on [0,1] with underlying distributions. Some stochastic orders are invariant with respect to these models.
Invariant copulas
Inverse distributions: the logarithmic case
In this paper it is proved that the distribution of the logarithmic series is not invertible while it is found to be invertible if corrected by a suitable affinity. The inverse distribution of the corrected logarithmic series is then derived. Moreover the asymptotic behaviour of the variance function of the logarithmic distribution is determined. It is also proved that the variance function of the inverse distribution of the corrected logarithmic distribution has a cubic asymptotic behaviour.
Isoperimetric problem for uniform enlargement
We consider an isoperimetric problem for product measures with respect to the uniform enlargement of sets. As an example, we find (asymptotically) extremal sets for the infinite product of the exponential measure.
Jacobi radial stable processes
Joint weak hazard rate order under non-symmetric copulas
A weak version of the joint hazard rate order, useful to stochastically compare not independent random variables, has been recently defined and studied in [4]. In the present paper, further results on this order are proved and discussed. In particular, some statements dealing with the relationships between the jointweak hazard rate order and other stochastic orders are generalized to the case of non symmetric copulas, and its relations with some multivariate aging notions (studied in [2]) are presented....
Józef Marcinkiewicz (1910-1940) - on the centenary of his birth
Józef Marcinkiewicz’s (1910-1940) name is not known by many people, except maybe a small group of mathematicians, although his influence on the analysis and probability theory of the twentieth century was enormous. This survey of his life and work is in honour of the anniversary of his birth and anniversary of his death. The discussion is divided into two periods of Marcinkiewicz’s life. First, 1910-1933, that is, from his birth to his graduation from the University of Stefan Batory in Vilnius,...
Józef Marcinkiewicz: analysis and probability
We briefly review Marcinkiewicz's work, on analysis, on probability, and on the interplay between the two. Our emphasis is on the continuing vitality of Marcinkiewicz's work, as evidenced by its influence on the standard works. What is striking is how many of the themes that Marcinkiewicz studied (alone, or with Zygmund) are very much alive today. What this demonstrates is that Marcinkiewicz and Zygmund, as well as having extraordinary mathematical ability, also had excellent mathematical taste.
Kernel estimators and the Dvoretzky-Kiefer-Wolfowitz inequality
It turns out that for standard kernel estimators no inequality like that of Dvoretzky-Kiefer-Wolfowitz can be constructed, and as a result it is impossible to answer the question of how many observations are needed to guarantee a prescribed level of accuracy of the estimator. A remedy is to adapt the bandwidth to the sample at hand.
-norm of infinitely divisible random vectors and certain stochastic integrals.
-Khintchine-Bonami inequality in free probability
We prove the norm estimates for operator-valued functions on free groups supported on the words with fixed length (). Next, we replace the translations by the free generators with a free family of operators and prove inequalities of the same type.
inequalities for functionals of brownian motion
La convergence de la série de Picard pour les EDS