12 citations · 17 across the 8 of their papers we have counts for
8 papers
Inequalities for m-Divisible Distributions and Testing of Infinite Divisibility
Lev B. Klebanov, Ashot V. Kakosyan, Irina V. Volchenkova
We state some inequalities for m-divisible and infinite divisible characteristic functions. Basing on them we propose a statistical test for a distribution to be infinitely divisib…
Characterization of multivariate distributions by means of univariate one
Lev B. Klebanov, Irina V. Volchenkova
The aim of this paper is to show a possibility to identify multivariate distribution by means of specially constructed one-dimensional random variable. We give some inequalities wh…
Outliers and The Ostensibly Heavy Tails
Lev B. Klebanov, Irina Volchenkova
The aim of the paper is to show that the presence of one possible type of outliers is not connected to that of heavy tails of the distribution. In contrary, typical situation for o…
A new convexity-based inequality, characterization of probability distributions and some free-of-distribution tests
Lev B. Klebanov, Irina V. Volchenkova
A new inequality between some functional of probability distribution functions is given. The inequality is based on strict convexity of a function used in functional definition. Eq…
A method of induction the distances with Hilbert structure
Vesna Gotovac, Katerina Helisova, Lev B. Klebanov +1
A method of induction the distances with Hilbert structure is proposed. Some properties of the method are studied. Typical examples of corresponding metric spaces are discussed. Ke…
A new definition of random sets
Vesna Gotovac, Kateřina Helisova, Lev B. Klebanov +1
A new definition of random sets is proposed. It is based on the distance in measurable space and uses negative definite kernels for continuation from initial space to that of rando…
On a characterization of infinitely divisible distributions with Gaussian component
Lev B. Klebanov, Irina V. Volchenkova, Ashot V. Kakosyan
We give a necessary and sufficient condition for symmetric infinitely divisible distribution to have Gaussian component. The result can be applied to approximation the distribution…
Heavy Tailed Distributions in Finance: Reality or Myth? Amateurs Viewpoint
Lev B Klebanov, Irina V Volchenkova
The purpose of this paper is to show that the use of heavy-tailed distributions in Financial problems is theoretically baseless and can lead to significant misunderstandings. The r…