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Suppose we observe a trajectory of length $n$ from an exponentially $\alpha$-mixing stochastic process over a finite but potentially large state space. We consider the problem of estimating the probability mass placed by the stationary…

Machine Learning · Statistics 2025-06-09 Milind Nakul , Vidya Muthukumar , Ashwin Pananjady

The aim of this paper is to provide conditions which ensure that the affinely transformed partial sums of a strictly stationary process converge in distribution to an infinite variance stable distribution. Conditions for this convergence to…

Probability · Mathematics 2011-10-20 Katarzyna Bartkiewicz , Adam Jakubowski , Thomas Mikosch , Olivier Wintenberger

In this article, we consider Poisson and Poisson convoluted geometric approximation to the sums of $n$ independent random variables under moment conditions. We use Stein's method to derive the approximation results in total variation…

Probability · Mathematics 2020-07-07 Pratima Eknath Kadu

Random events in space and time often exhibit a locally dependent structure. When the events are very rare and dependent structure is not too complicated, various studies in the literature have shown that Poisson and compound Poisson…

Probability · Mathematics 2011-02-22 Aihua Xia , Fuxi Zhang

Based on Stein's method, we derive upper bounds for Poisson process approximation in the $L_1$-Wasserstein metric $d_2^{(p)}$, which is based on a slightly adapted $L_p$-Wasserstein metric between point measures. For the case $p=1$, this…

Probability · Mathematics 2009-06-12 Dominic Schuhmacher

In this paper, we study numerical approximations for optimal control of a class of stochastic partial differential equations with partial observations. The system state evolves in a Hilbert space, whereas observations are given in…

Optimization and Control · Mathematics 2025-04-02 Feng Bao , Yanzhao Cao , Hongjiang Qian

We derive and analyze new diffusion approximations of stationary distributions of Markov chains that are based on second- and higher-order terms in the expansion of the Markov chain generator. Our approximations achieve a higher degree of…

Probability · Mathematics 2022-07-12 Anton Braverman , J. G. Dai , Xiao Fang

In this paper, we obtain error bound for binomial and negative binomial approximations to weighted sums of locally dependent random variables, using Stein's method. We also discuss approximation results for weighted sums of independent…

Probability · Mathematics 2020-10-20 Amit N. Kumar

We study average case approximation of Euler and Wiener integrated processes of d variables which are almost surely r_k-times continuously differentiable with respect to the k-th variable. Let n(h,d) denote the minimal number of continuous…

Probability · Mathematics 2012-12-04 M. A. Lifshits , A. Papageorgiou , H. Woźniakowski

Consider a stationary, weakly dependent sequence of random variables. Given only mild conditions, allowing for polynomial decay of the autocovariance function, we show a Berry-Esseen bound of optimal order $n^{-1/2}$ for studentized…

Probability · Mathematics 2025-04-22 Moritz Jirak

Let F ($\nu$) be the centered Gamma law with parameter $\nu$ > 0 and let us denote by P Y the probability distribution of a random vector Y. We develop a multidimensional variant of the Stein's method for Gamma approximation that allows to…

Probability · Mathematics 2023-05-10 Ciprian A Tudor , Jérémy Zurcher

Quantitative limit theorems for non-linear functionals on the Wiener space are considered. Given the possibly infinite sequence of kernels of the chaos decomposition of such a functional, an estimate for different probability distances…

Probability · Mathematics 2016-10-06 Tobias Fissler , Christoph Thaele

In this paper we deal with pointwise approximation of solutions of stochastic differential equations (SDEs) driven by infinite dimensional Wiener process with additional jumps generated by Poisson random measure. The further investigations…

Probability · Mathematics 2022-05-04 Paweł Przybyłowicz , Michał Sobieraj , Łukasz Stȩpień

We consider Grenander type estimators for monotone functions $f$ in a very general setting, which includes estimation of monotone regression curves, monotone densities, and monotone failure rates. These estimators are defined as the…

Statistics Theory · Mathematics 2014-10-09 Cécile Durot , Hendrik P. Lopuhaä

A specific family of point processes are introduced that allow to select samples for the purpose of estimating the mean or the integral of a function of a real variable. These processes, called quasi-systematic processes, depend on a tuning…

Methodology · Statistics 2016-07-19 Matthieu Wilhelm , Yves Tillé , Lionel Qualité

In [16], under mild conditions, a Wiener-Hopf type factorization is derived for the exponential functional of proper L\'evy processes. In this paper, we extend this factorization by relaxing a finite moment assumption as well as by…

Probability · Mathematics 2011-07-05 Pierre Patie , Mladen Savov

In this note we (in particular) prove an almost sure invariance principle (ASIP) for non-stationary and uniformly bounded sequences of random variables which are exponentially fast $\phi$-mixing. The obtained rate is of order…

Probability · Mathematics 2022-07-19 Yeor Hafouta

The aim of this paper is to present a result of discrete approximation of some class of stable self-similar stationary increments processes. The properties of such processes were intensively investigated, but little is known on the context…

Probability · Mathematics 2008-01-18 Clément Dombry , Nadine Guillotin-Plantard

Via a Bismut-Elworthy-Li formula from [KPP23], we derive uniform gradient estimates for transition semigroups associated with stochastic differential equations driven by a large class of cylindrical L\'{e}vy processes which includes the…

Probability · Mathematics 2025-09-09 Thanh Dang , Lingjiong Zhu

This paper studies a method, which has been proposed in the Physics literature by [8, 7, 10], for estimating the quasi-stationary distribution. In contrast to existing methods in eigenvector estimation, the method eliminates the need for…

Probability · Mathematics 2014-01-03 Jose Blanchet , Peter Glynn , Shuheng Zheng