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20172026
most citedAsymptotic and non-asymptotic estimates for multivariate Laplace integrals

1 citations · 2 across the 36 of their papers we have counts for

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13 papers · 1 filter

math.FA2022

Relations between Lorentz-Zygmund and Grand Lebesgue Spaces and norms

Maria Rosaria Formica, Eugeny Ostrovsky, Leonid Sirota

We establish imbedding properties between Grand Lebesgue Spaces and (generalized) Lorentz-Zygmund ones. We extend some known previous results concerning imbedding theorems between…

math.FA2022

Generalized Grand Lebesgue Spaces norm estimations for some operators

M. R. Formica, E. Ostrovsky, L. Sirota

We study moment rearrangement invariant spaces, which contain as particular cases the generalized Grand Lebesgue Spaces, and provide norm estimates for some operators, not necessar…

math.AP2022

Quasilinear P.D.Es, Interpolation spaces and Hölderian mappings

Irshaad Ahmed, Alberto Fiorenza, Maria Rosaria Formica +3

As in the work of Tartar ( Tartar L. Interpolation non linéaire et régularité, 9, Journal of Functional Analysis, (1972), 469-489) we developed here some new results on non linear…

math.PR2022

Exponential exact estimation for maximum and minimum tail of distribution for non-Gaussian random vector

M. R. Formica, E. Ostrovsky, L. Sirota

We find the exponential exact two-terms non-asymptotic expression for the maximum and minimum distribution of a non-Gaussian, in general case, random vector.

math.PR2022

Tail estimates for random variables from interrelation between corresponding moments inequalities

M. R. Formica, E. Ostrovsky, L. Sirota

We derive the tail inequalities between two random variables starting from inequalities between its moment, or more generally between its Lebesgue-Riesz norms, which holds true on…

math.FA2022

Weighted Grand Lebesgue Spaces norm estimation for Hardy-Sobolev-Poincare-Wirtinger operators

M. R. Formica, E. Ostrovsky, L. Sirota

We extend the classical Hardy-Sobolev-Poincare-Wirtinger inequalities from the ordinary Lebesgue-Riesz spaces into the Grand Lebesgue ones, with exact constants evaluation.

math.PR2022

Low bounds for distribution of sums of independent centered random variables belonging to Grand Lebesgue Spaces

M. R. Formica, E. Ostrovsky, L. Sirota

We deduce in this short report the non-asymptotic for exponential tail of distribution for sums of independent centered random variables.

math.PR2022

Modified Bernstein's inequality for sums of independent random variables

M. R. Formica, E. Ostrovsky, L. Sirota

We modify the classical Bernstein's inequality for the sums of independent centered random variables (r.v.) in the terms of relative tails or moments. We built also some examples i…

math.PR2022

Generalization of tail inequalities for random variables, using in the martingale theory

M. R. Formica, E. Ostrovsky, L. Sirota

We generalize a famous tail Doob's inequality, relative two non-negative random variables, arising in the martingale theory, in two directions: on the more general source data and…

math.PR2022

Moments and tail reciprocal connections for the random variables having generalized Gamma-Weibull distributions

M. R. Formica, E. Ostrovsky, L. Sirota

We establish the one-to one bilateral interrelations between an asymptotic behavior for the tail of distributions for random variables and its great moments evaluation. Our results…

math.PR2022

Tail estimations for normed sums of centered exchangeable random variables

M. R. Formica, E. Ostrovsky, L. Sirota

We derive in this short report the exponential as well as power decreasing tail estimations for the sums of centered exchangeable random variables, alike ones for the sums of the c…

math.FA2022

A note about extension of functions belonging to Sobolev-Grand Lebesgue Spaces

M. R. Formica, E. Ostrovsky, L. Sirota

We deduce an extension theorem for the so-called Sobolev-Grand Lebesgue Spaces defined on the suitable subsets of the whole finite-dimensional Euclidean space, and estimate the nor…

math.PR2022

Averaging of random variables and fields

M. R. Formica, E. Ostrovsky, L. Sirota

We will prove that by averaging of random variables (r.v.) and random fields (r.f.) its tails of distributions do not increase in comparison with the tails of source variables, ess…