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We describe a procedure to introduce general dependence structures on a set of Dirichlet processes. Dependence can be in one direction to define a time series or in two directions to define spatial dependencies. More directions can also be…

Methodology · Statistics 2021-10-18 Luis E. Nieto-Barajas

We prove the compact law of the iterated logarithm for stationary and ergodic differences of (reverse or not) martingales taking values in a separable $2$-smooth Banach space (for instance a Hilbert space). Then, in the martingale case, the…

Probability · Mathematics 2015-04-14 Christophe Cuny

Ostrowski's theorem implies that $\log(x),\log(x+1),\ldots$ are algebraically independent over $\mathbb{C}(x)$. More generally, for a linear differential or difference equation, it is an important problem to find all algebraic dependencies…

Commutative Algebra · Mathematics 2019-08-15 Alexey Ovchinnikov , Michael Wibmer

In this paper, by introducing a new type asymptotic coupling by reflection, we explore the long time behavior of random probability measure flows associated with a large class of one-dimensional McKean-Vlasov SDEs with common noise.…

Probability · Mathematics 2024-01-17 Bao Jianhai , Wang Jian

We study statistical models for one-dimensional diffusions which are recurrent null. A first parameter in the drift is the principal one, and determines regular varying rates of convergence for the score and the information process. A…

Statistics Theory · Mathematics 2017-11-07 Reinhard Höpfner , Carina Zeller

If the log likelihood is approximately quadratic with constant Hessian, then the maximum likelihood estimator (MLE) is approximately normally distributed. No other assumptions are required. We do not need independent and identically…

Statistics Theory · Mathematics 2012-07-06 Charles J. Geyer

We explore two notions of stationary processes. The first is called a random-step Markov process in which the stationary process of states, $(X_i)_{i \in \mathbb{Z}}$ has a stationary coupling with an independent process on the positive…

Probability · Mathematics 2014-10-07 Neal Bushaw , Karen Gunderson , Steven Kalikow

This paper studies the asymptotic behaviour of the solution of a differential equation perturbed by a fast flow preserving an infinite measure. This question is related with limit theorems for non-stationary Birkhoff integrals. We…

Dynamical Systems · Mathematics 2024-08-07 Maxence Phalempin

Under an appropriate regular variation condition, the affinely normalized partial sums of a sequence of independent and identically distributed random variables converges weakly to a non-Gaussian stable random variable. A functional version…

Probability · Mathematics 2012-10-12 Bojan Basrak , Danijel Krizmanić , Johan Segers

We consider a new class of determinantal point processes in the complex plane coming from the ground state of free fermions associated with Berezin--Toeplitz operators. These processes generalize the Ginibre ensemble from random matrix…

Probability · Mathematics 2025-08-15 Alix Deleporte , Gaultier Lambert

A set of coupled time-dependent Ginzburg-Landau equations (TDGL) for superconductors of mixed d- and s-wave symmetry are derived microscopically from the Gor'kov equations by using the analytical continuation technique. The scattering…

Superconductivity · Physics 2009-10-31 Jian-Xin Zhu , W. Kim , C. S. Ting , Chia-Ren Hu

We prove a fluctuating limit theorem of a sequence of super-Brownian motions over $\mbb{R}$ with a single point catalyst. The weak convergence of the processes on the space of Schwarz distributions is established. The limiting process is an…

Probability · Mathematics 2014-10-21 Zenghu Li , Li Wang

A Markov-switching observation-driven model is a stochastic process $((S_t,Y_t))_{t \in \mathbb{Z}}$ where $(S_t)_{t \in \mathbb{Z}}$ is an unobserved Markov chain on a finite set and $(Y_t)_{t \in \mathbb{Z}}$ is an observed stochastic…

Econometrics · Economics 2025-12-30 Frederik Krabbe

We prove a law of large numbers and a functional central limit theorem for the empirical density of a Marcus-Lushnikov model. The limiting density turns out to be the solution of a Smoluchowski equation, and the fluctuations around this…

Probability · Mathematics 2026-03-30 Julian Amorim , Arturo Arellano , Milton Jara

By a classical result of Weyl, for any increasing sequence $(n_k)_{k \geq 1}$ of integers the sequence of fractional parts $(\{n_k x\})_{k \geq 1}$ is uniformly distributed modulo 1 for almost all $x \in [0,1]$. Except for a few special…

Number Theory · Mathematics 2013-07-26 Christoph Aistleitner

We consider a linear mixed-effects model with a clustered structure, where the parameters are estimated using maximum likelihood (ML) based on possibly unbalanced data. Inference with this model is typically done based on asymptotic theory,…

Statistics Theory · Mathematics 2021-03-30 Chih-Hao Chang , Hsin-Cheng Huang , Ching-Kang Ing

Based on a martingale theory approach, we present a complete characterization of the asymptotic behaviour of a lazy reinforced random walk (LRRW) which shows three different regimes (diffusive, critical and superdiffusive). This allows us…

Ostrovskii's generalization of the Marcinkiewicz theorem implies that if an entire characteristic functions of a probability distribution satisfies $\log^+\log|f(z)|=o(|z|),\; z\to\infty,$ and is zero-free then the distribution is normal.…

Probability · Mathematics 2022-08-12 Alexandre Eremenko , Alexander Fryntov

Beginning with work of Zeilberger on classical pattern counts, there are a variety of structural results for moments of permutation statistics applied to random permutations. Using tools from representation theory, Gaetz and Ryba…

Combinatorics · Mathematics 2025-03-25 Zachary Hamaker , Brendon Rhoades

Stochastic gradient Langevin dynamics (SGLD) is a computationally efficient sampler for Bayesian posterior inference given a large scale dataset. Although SGLD is designed for unbounded random variables, many practical models incorporate…

Machine Learning · Statistics 2019-06-21 Soma Yokoi , Takuma Otsuka , Issei Sato