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Related papers: Sharp moment estimates for polynomial martingales

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In this paper we obtain the non-asymptotic exact moment and tails estimates for polynomial on martingale differences. We give also some examples on order to show the exactness of obtained results.

Probability · Mathematics 2011-12-14 E. Ostrovsky , L. Sirota

In this paper non-asymptotic exponential and moment estimates are derived for tail of distribution for discrete time martingale and martingale transform by means of martingale differences in the terms of moments and tails of distributions…

Probability · Mathematics 2012-06-22 E. Ostrovsky , L. Sirota

We obtain in this paper a non-asymptotic non-improvable up to multiplicative constant moment and exponential tail estimates for distribution for U-statistics by means of martingale representation. We show also the exactness of obtained…

Statistics Theory · Mathematics 2016-02-02 E. Ostrovsky , L. Sirota

In this paper non-asymptotic exponential and moment estimates are derived for tail of distribution for discrete time martingale under norming sequence 1/n, as in the classical Law of Large Numbers (LLN), by means of martingale differences…

Probability · Mathematics 2012-07-10 E. Ostrovsky , L. Sirota

In this paper non-asymptotic exponential estimates are derived for the tail distribution of polynomial martingale differences in terms unconditional tails distributions of summands. Applications are considered in the theory of polynomials…

Probability · Mathematics 2007-05-23 Eugene Ostrovsky

We derive the sharp non-asymptotical uniform estimations for tails of distributions for classical normed sums of centered normed independent random vectors having a moderate decreasing individual tails of summands.

Probability · Mathematics 2021-10-08 M. R. Formica , E. Ostrovsky , L. Sirota

In this paper non-asymptotic exponential estimates are derived for tail of maximum martingale distribution by naturally norming in the spirit of the classical Law of Iterated Logarithm. Key words: Martingales, exponential estimations,…

Probability · Mathematics 2008-01-15 E. Ostrovsky , L. Sirota

We provide sharp bounds for the exponential moments and $p$-moments, $1\leqslant p \leqslant 2$, of the terminate distribution of a martingale whose square function is uniformly bounded by one. We introduce a Bellman function for the…

Probability · Mathematics 2022-08-09 Dmitriy Stolyarov , Vasily Vasyunin , Pavel Zatitskiy , Ilya Zlotnikov

We derive sharp non - asymptotical Lebesgue - Riesz as well as Grand Lebesgue Space norm estimations for different norms of matrix martingales through these norms for the correspondent martingale differences and through the entropic…

Probability · Mathematics 2024-01-25 Maria Rosaria Formica , Eugeny Ostrovsky , Leonid Sirota

We derive two-sided bounds for moments and tails of random quadratic forms (random chaoses of order $2$), generated by independent symmetric random variables such that $\lVert X \rVert_{2p} \leq \alpha \lVert X \rVert_p$ for any $p\geq 1$…

Probability · Mathematics 2021-01-14 Rafał Meller

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 certain sets of parameters. We consider some applications…

Probability · Mathematics 2022-06-06 M. R. Formica , E. Ostrovsky , L. Sirota

We present two-sided estimates of moments and tails of polynomial chaoses of order at most three generated by independent symmetric random variables with log-concave tails as well as for chaoses of arbitrary order generated by independent…

Probability · Mathematics 2015-01-06 Radosław Adamczak , Rafał Latała

In this paper we consider the semi-parametric estimation of extreme quantiles of a right heavy-tail model. We propose a new Log Probability Weighted Moment estimator for extreme quantiles, which is obtained from the estimators of the shape…

Methodology · Statistics 2014-01-16 Frederico Caeiro , Dora Prata Gomes

We investigate the relation between moments and tails of heavy-tailed (in particular, Pareto-type) distributions. We also discuss the sharpness of our results in a number of examples under certain regularity conditions like log-convexity.…

Probability · Mathematics 2024-10-30 Paul Buterus , Holger Sambale

In this note we give a combinatorial and non-computational proof of the asymptotics of the integer moments of the moments of the characteristic polynomials of Haar distributed unitary matrices as the size of the matrix goes to infinity.…

Probability · Mathematics 2020-02-18 Theodoros Assiotis , Jonathan P. Keating

We derive two-sided estimates for random multilinear forms (random chaoses) generated by independent symmetric random variables with logarithmically concave tails. Estimates are exact up to multiplicative constants depending only on the…

Probability · Mathematics 2016-04-05 Konrad Kolesko , Rafał Latała

We establish sharp large deviation asymptotics for the maximum order statistic of independent and identically distributed heavy-tailed random variables, valid for all Borel subsets of the right tail. This result yields exact decay rates for…

Probability · Mathematics 2026-01-09 José M. Zapata

In the world of multivariate extremes, estimation of the dependence structure still presents a challenge and an interesting problem. A procedure for the bivariate case is presented that opens the road to a similar way of handling the…

Statistics Theory · Mathematics 2008-11-14 John H. J. Einmahl , Andrea Krajina , Johan Segers

We deduce in this paper the sufficient conditions for weak convergence of centered and normed deviation of the u-statistics with values in the space of the real valued continuous function defined on some compact metric space. We obtain also…

Statistics Theory · Mathematics 2016-08-12 E. Ostrovsky , L. Sirota

We extend some known results relating the distribution tails of a continuous local martingale supremum and its quadratic variation to the case of locally square integrable martingales with bounded jumps. The predictable and optional…

Probability · Mathematics 2007-05-23 R. Liptser , A. Novikov
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