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In this paper, we study the L\'evy process time-changed by independent L\'evy subordinators, namely, the incomplete gamma subordinator, the $\epsilon$-jumps incomplete gamma subordinator and tempered incomplete gamma subordinator. We derive…

Probability · Mathematics 2024-05-17 Meena Sanjay Babulal , Sunil Kumar Gauttam , Aditya Maheshwari

We consider continuous-time Markov chains on integers which allow transitions to adjacent states only, with alternating rates. We give explicit formulas for probability generating functions, and also for means, variances and state…

Probability · Mathematics 2019-10-30 Luisa Beghin , Claudio Macci , Barbara Martinucci

The purpose of the present paper is to establish moderate deviation principles for a rather general class of random variables fulfilling certain bounds of the cumulants. We apply a celebrated lemma of the theory of large deviations…

Probability · Mathematics 2012-09-28 Hanna Doering , Peter Eichelsbacher

This is basically a polished presentation for Sections 1,2 of arXiv:0801.1050. The Moderate Deviations Principle (MDP) is well-understood for sums of independent random variables, worse understood for stationary random sequences, and…

Probability · Mathematics 2016-12-28 Boris Tsirelson

We prove that moderate deviations for empirical measures for countable nonhomogeneous Markov chains hold under the assumption of uniform convergence of transition probability matrices for countable nonhomogeneous Markov chains in Ces\`aro…

Probability · Mathematics 2020-10-16 Mingzhou Xu , Kun Cheng

We consider time-changed Poisson processes, and derive the governing difference-differential equations (DDE) these processes. In particular, we consider the time-changed Poisson processes where the the time-change is inverse Gaussian, or…

Probability · Mathematics 2011-10-14 A. Kumar , Erkan Nane , P. Vellaisamy

In this paper we derive the moderate deviation principle for stationary sequences of bounded random variables under martingale-type conditions. Applications to functions of $\phi$-mixing sequences, contracting Markov chains, expanding maps…

Probability · Mathematics 2007-11-27 Jérôme Dedecker , Florence Merlevède , Magda Peligrad , Sergey Utev

In this article, the problem of semi-parametric inference on the parameters of a multidimensional L\'{e}vy process $L_t$ with independent components based on the low-frequency observations of the corresponding time-changed L\'{e}vy process…

Methodology · Statistics 2012-01-31 Denis Belomestny

This article is devoted to some time-changed stochastic models based on multivariate stable processes. The considered models have several advantages in comparison with classical time-changed Brownian motions - for instance, it turns out…

Probability · Mathematics 2018-06-12 V. Panov , E. Samarin

Standard GPs offer a flexible modelling tool for well-behaved processes. However, deviations from Gaussianity are expected to appear in real world datasets, with structural outliers and shocks routinely observed. In these cases GPs can fail…

Machine Learning · Statistics 2022-09-08 Yaman Kındap , Simon Godsill

The purpose of this paper is to investigate the deviation inequalities and the moderate deviation principle of the least squares estimators of the unknown parameters of general $p$th-order bifurcating autoregressive processes, under…

Probability · Mathematics 2012-04-12 Hacène Djellout , Valère Bitseki Penda

This paper studies a time-changed stochastic control problem, where the underlying stochastic process is a L\'evy noise time-changed by an inverse subordinator. We establish a maximum principle theory for the time-changed stochastic control…

Probability · Mathematics 2019-05-29 Erkan Nane , Yinan Ni

L\'evy processes, known for their ability to model complex dynamics with skewness, heavy tails and discontinuities, play a critical role in stochastic modeling across various domains. However, inference for most L\'evy processes, whether in…

Methodology · Statistics 2025-05-29 Bill Z. Lin , Simon Godsill

An example of a discrete-time stationary random process whose sums follow the normal approximation within a given part of the region of moderate deviations, but violate it outside this part.

Probability · Mathematics 2012-07-23 Boris Tsirelson

We provide asymptotic results and develop high frequency statistical procedures for time-changed L\'evy processes sampled at random instants. The sampling times are given by first hitting times of symmetric barriers whose distance with…

Probability · Mathematics 2010-07-20 Mathieu Rosenbaum , Peter Tankov

We consider a single-server queue where interarrival and service times depend linearly and randomly on customer waiting times, and establish a sample-path moderate deviation principle (MDP) for the waiting time process. The waiting times…

Probability · Mathematics 2025-11-03 Chang Feng , John J. Hasenbein , Guodong Pang

A moderate deviation principle for functionals, with at most quadratic growth, of moving average processes is established. The main assumptions on the moving average process are a Logarithmic Sobolev inequality for the driving random…

Probability · Mathematics 2007-06-13 Hacene Djellout , Arnaud Guillin , Liming Wu

The main results in this paper concern large deviations for families of non-Gaussian processes obtained as suitable perturbations of continuous centered multivariate Gaussian processes which satisfy a large deviation principle. We present…

Probability · Mathematics 2023-07-06 C. Macci , B. Pacchiarotti

In this paper, we prove the moderate deviations principle (MDP) for a general system of slow-fast dynamics. We provide a unified approach, based on weak convergence ideas and stochastic control arguments, that cover both the averaging and…

Probability · Mathematics 2017-06-02 Matthew R. Morse , Konstantinos Spiliopoulos

We consider a collection of fully coupled weakly interacting diffusion processes moving in a two-scale environment. We study the moderate deviations principle of the empirical distribution of the particles' positions in the combined limit…

Probability · Mathematics 2023-07-17 Zachary Bezemek , Konstantinos Spiliopoulos