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In this paper we prove necessary conditions for the boundedness of fractional operators on the variable Lebesgue spaces. More precisely, we find necessary conditions on an exponent function $\pp$ for a fractional maximal operator $M_\alpha$…

Classical Analysis and ODEs · Mathematics 2024-08-26 David Cruz-Uribe , Troy Roberts

Consider the partial sums {S_t} of a real-valued functional F(Phi(t)) of a Markov chain {Phi(t)} with values in a general state space. Assuming only that the Markov chain is geometrically ergodic and that the functional F is bounded, the…

Probability · Mathematics 2007-05-23 Ioannis Kontoyiannis , Sean Meyn

We provide a condition for f-ergodicity of strong Markov processes at a subgeometric rate. This condition is couched in terms of a supermartingale property for a functional of the Markov process. Equivalent formulations in terms of a drift…

Statistics Theory · Mathematics 2007-06-13 Randal Douc , Gersende Fort , Arnaud Guillin

We discuss complementary recurrence and transience criteria for stochastic processes $(X_n)_{n \ge 0}$ with values in the $d$-dimensional orthant $\mathbb R^d_+$ fulfilling a non-linear stochastic equation of the form $X_{n+1}=MX_n+g(X_n)+…

Probability · Mathematics 2016-04-05 Götz Kersting

We consider the Markov chain approximations for singular stable-like processes. First we obtain properties of some Markov chains. Then we construct the approximating Markov chains and give a necessary condition for weak convergence of these…

Probability · Mathematics 2012-10-11 Fangjun Xu

The famous results of Koml\'os, Major and Tusn\'ady (see [15] and [17]) state that it is possible to approximate almost surely the partial sums of size n of i.i.d. centered random variables in L p (p > 2) by a Wiener process with an error…

Probability · Mathematics 2017-06-27 Christophe Cuny , Jérôme Dedecker , Florence Merlevède

We study continuous-time Markov chains on the non-negative integers under mild regularity conditions (in particular, the set of jump vectors is finite and both forward and backward jumps are possible). Based on the so-called flux balance…

Probability · Mathematics 2024-11-26 Mads Chr Hansen , Carsten Wiuf , Chuang Xu

Stochastic integrals are defined with respect to a collection $P = (P_i; \, i \in I)$ of continuous semimartingales, imposing no assumptions on the index set $I$ and the subspace of $\mathbb{R}^I$ where $P$ takes values. The integrals are…

Probability · Mathematics 2019-08-20 Constantinos Kardaras

The Gibbs sampler (GS) is a crucial algorithm for approximating complex calculations, and it is justified by Markov chain theory, the alternating projection theorem, and $I$-projection, separately. We explore the equivalence between these…

Computation · Statistics 2024-10-15 Kun-Lin Kuo , Yuchung J. Wang

There has been recent interest in the conditional central limit question for (strictly) stationary, ergodic processes $...,X_{-1},X_0,X_1,...$ whose partial sums $S_n=X_1+...+X_n$ are of the form $S_n=M_n+R_n$, where $M_n$ is a square…

Probability · Mathematics 2008-01-03 Ou Zhao , Michael Woodroofe

For a class of symmetric random matrices whose entries are martingale differences adapted to an increasing filtration, we prove that under a Lindeberg-like condition, the empirical spectral distribution behaves asymptotically similarly to a…

Probability · Mathematics 2014-02-27 Florence Merlevède , Costel Peligrad , Magda Peligrad

Let $\mathcal{G}$ be a directed graph with vertices $1,2,\ldots, 2N$. Let $\mathcal{T}=(T_{i,j})_{(i,j)\in\mathcal{G}}$ be a family of contractive similitudes. For every $1\leq i\leq N$, let $i^+:=i+N$. For $1\leq i,j\leq N$, we define…

Functional Analysis · Mathematics 2023-07-12 Sanguo Zhu

Linear two-timescale stochastic approximation (SA) scheme is an important class of algorithms which has become popular in reinforcement learning (RL), particularly for the policy evaluation problem. Recently, a number of works have been…

Machine Learning · Statistics 2020-02-05 Maxim Kaledin , Eric Moulines , Alexey Naumov , Vladislav Tadic , Hoi-To Wai

For general, almost surely absorbed Markov processes, we obtain necessary and sufficient conditions for exponential convergence to a unique quasi-stationary distribution in the total variation norm. These conditions also ensure the…

Probability · Mathematics 2014-12-25 Nicolas Champagnat , Denis Villemonais

We consider a Markov chain X_1, X_2, ..., X_n belonging to a class of iterated random functions, which is "one-step contracting" with respect to some distance d. If f is any separately Lipschitz function with respect to d, we use a well…

Probability · Mathematics 2014-02-18 Jérôme Dedecker , Xiequan Fan

We show that the classical $A_{\infty}$ condition is not sufficient for a lower square function estimate in the non-homogeneous weighted $L^2$ space. We also show that under the martingale $A_2$ condition, an estimate holds true, but the…

Analysis of PDEs · Mathematics 2017-05-24 K. Domelevo , P. Ivanisvili , S. Petermichl , S. Treil , A. Volberg

In the paper we study sharp maximal inequalities for martingales and non-negative submartingales: if $f$, $g$ are martingales satisfying \[|\mathrm{d}g_n|\leq|\mathrm{d}f_n|,\qquad n=0,1,2,...,\] almost surely, then…

Statistics Theory · Mathematics 2012-01-06 Adam Osȩkowski

We work under the A\"{\i}d\'{e}kon-Chen conditions which ensure that the derivative martingale in a supercritical branching random walk on the line converges almost surely to a nondegenerate nonnegative random variable that we denote by…

Probability · Mathematics 2020-02-14 Dariusz Buraczewski , Alexander Iksanov , Bastien Mallein

In the present paper we obtain sufficient conditions for the existence of equivalent martingale measures for L\'{e}vy-driven moving averages and other non-Markovian jump processes. The conditions that we obtain are, under mild assumptions,…

Probability · Mathematics 2017-04-28 Andreas Basse-O'Connor , Mikkel Slot Nielsen , Jan Pedersen

The paper is concerned with approximating the distribution of a sum W of n integer valued random variables Y_i, whose distributions depend on the state of an underlying Markov chain X. The approximation is in terms of a translated Poisson…

Probability · Mathematics 2008-10-06 A. D. Barbour , Torgny Lindvall
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