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The use of an Ornstein-Uhlenbeck (OU) process is ubiquitous in business, economics and finance to capture various price processes and evolution of economic indicators exhibiting mean-reverting properties. When structural changes happen,…

Methodology · Statistics 2017-05-30 Fuqi Chen , Rogemar Mamon , Matt Davison

Dense Associative Memories or Modern Hopfield Networks have many appealing properties of associative memory. They can do pattern completion, store a large number of memories, and can be described using a recurrent neural network with a…

Neural and Evolutionary Computing · Computer Science 2021-07-29 Dmitry Krotov

This paper describes limiting behaviour of tail empirical process associated with long memory stochastic volatility models. We show that such process has dichotomous behaviour, according to an interplay between a Hurst parameter and a tail…

Statistics Theory · Mathematics 2010-11-23 Rafal Kulik , Philippe Soulier

We consider empirical multi-dimensional Rare Events Point Processes that keep track both of the time occurrence of extremal observations and of their severity, for stochastic processes arising from a dynamical system, by evaluating a given…

Dynamical Systems · Mathematics 2017-09-19 Ana Cristina Moreira Freitas , Jorge Milhazes Freitas , Mário Magalhães

The paper proposes an identification procedure for autoregressive gaussian stationary stochastic processes wherein the manifest (or observed) variables are mostly related through a limited number of latent (or hidden) variables. The method…

Optimization and Control · Mathematics 2014-12-02 Mattia Zorzi , Rodolphe Sepulchre

Hierarchical autocorrelation in the error term of linear models arises when sampling units are related to each other according to a tree. The residual covariance is parametrized using the tree-distance between sampling units. When…

Statistics Theory · Mathematics 2013-08-09 Lam Si Tung Ho , Cécile Ané

The generalized filtered method of moments was developed in the recent papers by Alomari et al., 2020, and Ayache et al., 2022. It used functional data obtained from continuously sampled cyclic long-memory stochastic processes to…

Statistics Theory · Mathematics 2024-07-18 Antoine Ayache , Serhii Kravchenko , Andriy Olenko

This work deals with a system of interacting reinforced stochastic processes, where each process $X^j=(X_{n,j})_n$ is located at a vertex $j$ of a finite weighted direct graph, and it can be interpreted as the sequence of "actions" adopted…

Probability · Mathematics 2020-09-10 Giacomo Aletti , Irene Crimaldi , Andrea Ghiglietti

We study a relaxation behavior of an Ornstein-Uhlenbeck (OU) process with a time-dependent and fluctuating diffusivity. In this process, the dynamics of a position vector is modeled by the Langevin equation with a linear restoring force and…

Statistical Mechanics · Physics 2019-03-27 Takashi Uneyama , Tomoshige Miyaguchi , Takuma Akimoto

The primate heteromodal cortex presents an evident functional modularity at a mesoscopic level, with physiological and anatomical evidence pointing to it as likely substrate of long-term memory. In order to investigate some of its…

Neurons and Cognition · Quantitative Biology 2021-12-09 Carlo Fulvi Mari

We study the asymptotic behavior of wavelet coefficients of random processes with long memory. These processes may be stationary or not and are obtained as the output of non--linear filter with Gaussian input. The wavelet coefficients that…

Probability · Mathematics 2010-07-28 Marianne Clausel , François Roueff , Murad S. Taqqu , Ciprian A. Tudor

From a continuous-time long memory stochastic process, a discrete-time randomly sampled one is drawn. We investigate the second-order properties of this process and establish some time-and frequency-domain asymptotic results. We mainly…

Statistics Theory · Mathematics 2021-10-12 Mohamedou Ould Haye , Anne Philippe , Caroline Robet

Stochastic point processes relevant to the theory of long-range aperiodic order are considered that display diffraction spectra of mixed type, with special emphasis on explicitly computable cases together with a unified approach of…

Mathematical Physics · Physics 2019-07-17 Michael Baake , Matthias Birkner , Robert V. Moody

For each $\lambda>0$ and every square-integrable infinitely-divisible (ID) distribution there exists at least one stationary stochastic process $t\mapsto X_t$ with the specified distribution for $X_1$ and with first-order autoregressive…

Probability · Mathematics 2021-06-02 Robert L Wolpert

This work is concerned with model reduction of stochastic differential equations and builds on the idea of replacing drift and noise coefficients of preselected relevant, e.g. slow variables by their conditional expectations. We extend…

Analysis of PDEs · Mathematics 2020-03-05 Carsten Hartmann , Lara Neureither , Upanshu Sharma

The $L^p$ maximal inequalities for martingales are one of the classical results in the theory of stochastic processes. Here we establish the sharp moderate maximal inequalities for one-dimensional diffusion processes, which include the…

Probability · Mathematics 2021-11-05 Xian Chen , Yong Chen , Mumien Cheng , Chen Jia

Reciprocal processes are acausal generalizations of Markov processes introduced by Bernstein in 1932. In the literature, a significant amount of attention has been focused on developing dynamical models for reciprocal processes. Recently,…

Machine Learning · Statistics 2018-04-11 Francesca Paola Carli

Assuming that a reflected Ornstein-Uhlenbeck state process is observed at discrete time instants, we propose generalized moment estimators to estimate all drift and diffusion parameters via the celebrated ergodic theorem. With the sampling…

Statistics Theory · Mathematics 2020-09-14 Yaozhong Hu , Yuejuan Xi

We study the asymptotic behaviour of partial sums of long range dependent random variables and that of their counting process, together with an appropriately normalized integral process of the sum of these two processes, the so-called…

Probability · Mathematics 2013-02-18 Endre Csáki , Miklós Csörgö , Rafal Kulik

Wavefield speckle patterns are generated by interference of randomly scattered coherent light. In the weak-coupling regime of the It\^o-Schr\"odinger paraxial model for long-distance wave propagation, we show the following multiscale…

Analysis of PDEs · Mathematics 2025-10-13 Guillaume Bal , Anjali Nair