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This article reviews recent advances in fixed effect estimation of panel data models for long panels, where the number of time periods is relatively large. We focus on semiparametric models with unobserved individual and time effects, where…

Econometrics · Economics 2018-03-29 Iván Fernández-Val , Martin Weidner

The purpose of the present work is to construct estimators for the random effects in a fractional diffusion model using a hybrid estimation method where we combine parametric and nonparametric thechniques. We precisely consider $n$…

Statistics Theory · Mathematics 2025-06-13 Nesrine Chebli , Hamdi Fathallah , Yousri Slaoui

The paper studies the counting process arising as a subset of births and deaths in a birth--death process on a finite state space. Whenever a birth or death occurs, the process is incremented or not depending on the outcome of an…

Probability · Mathematics 2026-01-13 Daryl. J. Daley , Yoni Nazarathy , Jiesen Wang

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

Studies of memory trajectories using longitudinal data often result in highly non-representative samples due to selective study enrollment and attrition. An additional bias comes from practice effects that result in improved or maintained…

Methodology · Statistics 2021-03-23 Maria Josefsson , Michael J. Daniels , Sara Pudas

The goal of this paper is to propose a new approach to asymptotic analysis of the finite predictor for stationary sequences. It produces the exact asymptotics of the relative prediction error and the partial correlation coefficients. The…

Statistics Theory · Mathematics 2025-04-03 P. Chigansky , M. Kleptsyna

This paper presents in detail the originally developed Quadratic Point Estimate Method (QPEM), aimed at efficiently and accurately computing the first four output moments of probabilistic distributions, using 2n^2+1 sample (or sigma)…

Numerical Analysis · Mathematics 2024-03-21 Minhyeok Ko , Konstantinos G. Papakonstantinou

Long memory processes driven by L\'evy noise with finite second-order moments have been well studied in the literature. They form a very rich class of processes presenting an autocovariance function which decays like a power function. Here,…

Probability · Mathematics 2022-04-20 G. L. Feltes , S. R. C. Lopes

Wavelet-type random series representations of the well-known Fractional Brownian Motion (FBM) and many other related stochastic processes and fields have started to be introduced since more than two decades. Such representations provide…

Probability · Mathematics 2023-03-10 Antoine Ayache , Julien Hamonier , Laurent Loosveldt

This paper provides yet another look at the mixed fractional Brownian motion (fBm), this time, from the spectral perspective. We derive an approximation for the eigenvalues of its covariance operator, asymptotically accurate up to the…

Probability · Mathematics 2019-12-25 P. Chigansky , M. Kleptsyna , D. Marushkevych

Estimating percentiles of black-box deterministic functions with random inputs is a challenging task when the number of function evaluations is severely restricted, which is typical for computer experiments. This article proposes two new…

Statistics Theory · Mathematics 2016-05-23 T Labopin-Richard , V Picheny

As an essential characteristics of fractional calculus, the memory effect is served as one of key factors to deal with diverse practical issues, thus has been received extensive attention since it was born. By combining the fractional…

Optimization and Control · Mathematics 2021-07-13 Wanli Xie , Wen-Ze Wu , Chong Liu , Mark Goh

Recently, we have proposed a new diffusive representation for fractional derivatives and, based on this representation, suggested an algorithm for their numerical computation. From the construction of the algorithm, it is immediately…

Numerical Analysis · Mathematics 2022-04-12 Kai Diethelm

We define and study the multiparameter fractional Brownian motion. This process is a generalization of both the classical fractional Brownian motion and the multiparameter Brownian motion, when the condition of independence is relaxed.…

Probability · Mathematics 2007-05-23 Erick Herbin , Ely Merzbach

Multifractional processes extend the concept of fractional Brownian motion by replacing the constant Hurst parameter with a time-varying Hurst function. This extension allows for modulation of the roughness of sample paths over time. The…

Probability · Mathematics 2025-03-11 Antoine Ayache , Andriy Olenko , Nemini Samarakoon

We describe a Bayesian framework for estimating the time-domain noise covariance of CMB observations, typically parametrized in terms of a 1/f frequency profile. This framework is based on the Gibbs sampling algorithm, which allows for…

Instrumentation and Methods for Astrophysics · Physics 2015-05-30 I. K. Wehus , S. K. Næss , H. K. Eriksen

For a multivariate stationary process, we develop explicit representations for the finite predictor coefficient matrices, the finite prediction error covariance matrices and the partial autocorrelation function (PACF) in terms of the…

Probability · Mathematics 2016-09-05 Akihiko Inoue , Yukio Kasahara , Mohsen Pourahmadi

Considering the large number of fractional operators that exist, and since it does not seem that their number will stop increasing soon at the time of writing this paper, it is presented for the first time, as far as the authors know, a…

Numerical Analysis · Mathematics 2024-03-27 A. Torres-Hernandez , F. Brambila-Paz

The paper deals with planar segment processes given by a density with respect to the Poisson process. Parametric models involve reference distributions of directions and/or lengths of segments. These distributions generally do not coincide…

Statistics Theory · Mathematics 2017-08-30 Viktor Benes , Jakub Vecera , Milan Pultar

Fractional-order dynamical systems are used to describe processes that exhibit long-term memory with power-law dependence. Notable examples include complex neurophysiological signals such as electroencephalogram (EEG) and blood-oxygen-level…

Optimization and Control · Mathematics 2018-10-04 Sarthak Chatterjee , Sérgio Pequito