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We obtain Stein approximation bounds for stochastic integrals with respect to a Poisson random measure over ${\Bbb R}^d$, $d\geq 2$. This approach relies on third cumulant Edgeworth-type expansions based on derivation operators defined by…

Probability · Mathematics 2018-06-04 Nicolas Privault

We derive two-sided bounds for moments of random multilinear forms (random chaoses) with nonnegative coeficients generated by independent nonnegative random variables $X_i$ which satisfy the following condition on the growth of moments:…

Probability · Mathematics 2016-12-13 Rafał Meller

We prove pointwise variational Lp bounds for a bilinear Fourier integral operator in a large but not necessarily sharp range of exponents. This result is a joint strengthening of the corresponding bounds for the classical Carleson operator,…

Classical Analysis and ODEs · Mathematics 2016-05-03 Yen Do , Camil Muscalu , Christoph Thiele

This paper deals with U-statistics of Poisson processes and multiple Wiener-It\^o integrals on the Poisson space. Via sharp bounds on the cumulants for both classes of random variables, moderate deviation principles, concentration…

Probability · Mathematics 2023-04-13 Matthias Schulte , Christoph Thaele

Bounds of the accuracy of the normal approximation to the distribution of a sum of independent random variables are improved under relaxed moment conditions, in particular, under the absence of moments of orders higher than the second.…

Probability · Mathematics 2015-07-06 V. Yu. Korolev , A. V. Dorofeeva

Modelling the first-order intensity function is one of the main aims in point process theory, and it has been approached so far from different perspectives. One appealing model describes the intensity as a function of a spatial covariate.…

Methodology · Statistics 2018-07-03 M. I. Borrajo , W. González-Manteiga , M. D. Martínez-Miranda

We consider sequences of random variables of the type $S_n= n^{-1/2} \sum_{k=1}^n \{f(X_k)-\E[f(X_k)]\}$, $n\geq 1$, where $X=(X_k)_{k\in \Z}$ is a $d$-dimensional Gaussian process and $f: \R^d \rightarrow \R$ is a measurable function. It…

Probability · Mathematics 2010-06-08 Ivan Nourdin , Giovanni Peccati , Mark Podolskij

In this paper, we establish moment and Bernstein-type inequalities for additive functionals of geometrically ergodic Markov chains. These inequalities extend the corresponding inequalities for independent random variables. Our conditions…

Probability · Mathematics 2023-06-16 Alain Durmus , Eric Moulines , Alexey Naumov , Sergey Samsonov

We establish presumably optimal rates of normal convergence with respect to the Kolmogorov distance for a large class of geometric functionals of marked Poisson and binomial point processes on general metric spaces. The rates are valid…

Probability · Mathematics 2017-02-03 Raphaël Lachièze-Rey , Matthias Schulte , J. E. Yukich

Ratios of random variables often appear in probability and statistical applications. We aim to approximate the moments of such ratios under several dependence assumptions. Extending the ideas in Collomb [C. R. Acad. Sci. Paris 285 (1977)…

Statistics Theory · Mathematics 2010-01-14 Paul Doukhan , Gabriel Lang

Second order approximate ancillaries have evolved as the primary ingredient for recent likelihood development in statistical inference. This uses quantile functions rather than the equivalent distribution functions, and the intrinsic…

Statistics Theory · Mathematics 2010-11-29 Ailana M. Fraser , D. A. S. Fraser , Ana-Maria Staicu

We explore connections between covariance representations, Bismut-type formulas and Stein's method. First, using the theory of closed symmetric forms, we derive covariance representations for several well-known probability measures on…

Probability · Mathematics 2023-07-06 Benjamin Arras , Christian Houdré

We deduce the non-asymptotical bilateral estimates for moment inequalities for sums of non-negative independent random variables, based on the correspondent estimates for the so-called Bell functions and the Poisson distribution.

Probability · Mathematics 2017-12-27 E. Ostrovsky , L. Sirota

This paper derives normal approximation results for subgraph counts written as multiparameter stochastic integrals in a random-connection model based on a Poisson point process. By combinatorial arguments we express the cumulants of general…

Probability · Mathematics 2025-11-11 Qingwei Liu , Nicolas Privault

We establish conditions for uniform $r$-th moment bound of certain $\R^d$-valued functions of a discrete-time stochastic process taking values in a general metric space. The conditions include an appropriate negative drift together with a…

Probability · Mathematics 2011-07-26 Arnab Ganguly , Debasish Chatterjee , John Lygeros , Heinz Koeppl

We derive in this preprint the moment and exponential tail estimates, sufficient conditions for the Non-Central Limit Theorem (NCLT) in the ordinary one-dimensional space as well as in the space of continuous functions for the properly…

Probability · Mathematics 2017-10-17 E. Ostrovsky , L. Sirota

It is well-known that assumptions of monotonicity in size-bias couplings may be used to prove simple, yet powerful, Poisson approximation results. Here we show how these assumptions may be relaxed, establishing explicit Poisson…

Probability · Mathematics 2019-01-30 Fraser Daly , Oliver Johnson

This work improves the existing central limit theorems (CLTs) for geometric functionals of Gibbs processes in three aspects. First, we derive a CLT for weakly stabilizing functionals, thereby improving on the previously used assumption of…

Probability · Mathematics 2024-06-12 Christian Hirsch , Moritz Otto , Anne Marie Svane

We provide Berry-Esseen bounds for sums of operator-valued Boolean and monotone independent variables, in terms of the first moments of the summands. Our bounds are on the level of Cauchy transforms as well as the L\'evy distance. As…

Probability · Mathematics 2022-11-16 Octavio Arizmendi , Marwa Banna , Pei-Lun Tseng

The purpose of the present paper is to establish moment estimates of Rosenthal type for a rather general class of random variables satisfying certain bounds on the cumulants. We consider sequences of random variables which satisfy a central…

Probability · Mathematics 2019-01-16 Peter Eichelsbacher , Lukas Knichel
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