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Based on the well-known Detrended Fluctuation Analysis (DFA) for time series, in this work we describe a DFA for continuous real variable functions. Under certain conditions, DFA accurately predicts the long-term auto-correlation of the…

Chaotic Dynamics · Physics 2023-04-11 Luis Gil-Maqueda , Benjamín A. Itzá-Ortiz

We propose a hybrid estimation procedure to estimate global fixed parameters and subject-specific random effects in a mixed fractional Black-Scholes model based on discrete-time observations. Specifically, we consider $N$ independent…

Statistics Theory · Mathematics 2026-02-13 Nesrine Chebli , Hamdi Fathallah , Yousri Slaoui

This paper develops the asymptotic theory for parametric and nonparametric regression models when the errors have a fractional local to unity root (FLUR) model structure. FLUR models are stationary time series with semi-long range…

Statistics Theory · Mathematics 2020-02-25 Farzad Sabzikar , Kris De Brabanter

We consider a simple mean reverting diffusion process, with piecewise constant drift and diffusion coefficients, discontinuous at a fixed threshold. We discuss estimation of drift and diffusion parameters from discrete observations of the…

Statistics Theory · Mathematics 2024-03-12 Sara Mazzonetto , Paolo Pigato

This paper investigates the second order properties of a stationary process after random sampling. While a short memory process gives always rise to a short memory one, we prove that long-memory can disappear when the sampling law has heavy…

Statistics Theory · Mathematics 2008-10-10 Anne Philippe , Marie-Claude Viano

Long and short memory in economic processes is usually described by the so-called discrete fractional differencing and fractional integration. We prove that the discrete fractional differencing and integration are the Grunwald-Letnikov…

Economics · Quantitative Finance 2017-08-08 Vasily E. Tarasov , Valentina V. Tarasova

We propose a new discrete-time online parameter estimation algorithm that combines two different aspects, one that adds momentum, and another that includes a time-varying learning rate. It is well known that recursive least squares based…

Optimization and Control · Mathematics 2023-03-21 Yingnan Cui , Anuradha M. Annaswamy

We present new mechanisms for \emph{label differential privacy}, a relaxation of differentially private machine learning that only protects the privacy of the labels in the training set. Our mechanisms cluster the examples in the training…

Machine Learning · Computer Science 2021-10-06 Hossein Esfandiari , Vahab Mirrokni , Umar Syed , Sergei Vassilvitskii

We develop a novel a posteriori error estimator for the $L^2$ error committed by the finite element discretization of the solution of the fractional Laplacian. Our a posteriori error estimator takes advantage of the semi-discretization…

Numerical Analysis · Mathematics 2023-03-14 Raphaël Bulle , Olga Barrera , Stéphane P. A. Bordas , Franz Chouly , Jack S. Hale

In this paper, the weak convergence about the discretization error of stochastic iterated integrals in the Skorohod sense are studied, while the integrands and integrators of iterated integrals are supposed to be semimartingales with jumps.…

Probability · Mathematics 2017-06-06 Yuping Song , Hanchao Wang

We present a family of generalized Hessian estimators of the objective using random direction stochastic approximation (RDSA) by utilizing only noisy function measurements. The form of each estimator and the order of the bias depend on the…

Machine Learning · Computer Science 2026-02-24 Soumen Pachal , Prashanth L. A. , Shalabh Bhatnagar , Avinash Achar

We consider the effects of long-range temporal correlations in many-particle systems, focusing particularly on fluctuations about the typical behaviour. For a specific class of memory dependence we discuss the modification of the large…

Statistical Mechanics · Physics 2015-12-24 Rosemary J. Harris

In this work, the motion of a dust particle under the influence of the random force due to dust charge fluctuations is considered as a non-Markovian stochastic process. Memory effects in the velocity process of the dust particle are…

Plasma Physics · Physics 2017-10-26 Zahra Ghannad , Hossein Hakimi Pajouh

A major issue in financial economics is the behavior of asset returns over long horizons. Various estimators of long range dependence have been proposed. Even though some have known asymptotic properties, it is important to test their…

Statistical Mechanics · Physics 2015-06-24 Rafal Weron

In this work, the uncertainty associated with the finite element discretization error is modeled following the Bayesian paradigm. First, a continuous formulation is derived, where a Gaussian process prior over the solution space is updated…

Numerical Analysis · Mathematics 2024-03-11 Anne Poot , Pierre Kerfriden , Iuri Rocha , Frans van der Meer

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by microscopy techniques. In this study, we present a…

Image and Video Processing · Electrical Eng. & Systems 2018-02-21 Rene Ledesma-Alonso , Romeli Barbosa , Jaime Ortegon

We propose two algorithms for discrete-time parameter estimation, one for time-varying parameters under persistent excitation (PE) condition, another for constant parameters under no PE condition. For the first algorithm, we show that in…

Machine Learning · Computer Science 2022-03-15 Yingnan Cui , Joseph E. Gaudio , Anuradha M. Annaswamy

This paper deals with the problem of inference associated with linear fractional diffusion process with random effects in the drift. In particular we are concerned with the maximum likelihood estimators (MLE) of the random effect…

Statistics Theory · Mathematics 2019-12-04 El Omari Mohamed , Hamid El Maroufy , Christiane Fuchs

In this paper, by comparing the time scales associated with the velocity relaxation and correlation time of the random force due to dust charge fluctuations, memory effects in the velocity relaxation of an isolated dust particle exposed to…

Plasma Physics · Physics 2017-04-27 Zahra Ghannad , Hossein Hakimi Pajouh

We investigate the statistics of eigenstates in a weak self-affine disordered potential in one dimension, whose Gaussian fluctuations grow with distance with a positive Hurst exponent $H$. Typical eigenstates are superlocalized on samples…

Statistical Mechanics · Physics 2007-05-23 J. M. Luck
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