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Given a discrete time sample $X_1,... X_n$ from a L\'evy process $X=(X_t)_{t\geq 0}$ of a finite jump activity, we study the problem of nonparametric estimation of the characteristic triplet $(\gamma,\sigma^2,\rho)$ corresponding to the…

Statistics Theory · Mathematics 2018-04-17 Shota Gugushvili

The free multiplicative Brownian motion $b_{t}$ is the large-$N$ limit of the Brownian motion on $\mathsf{GL}(N;\mathbb{C}),$ in the sense of $\ast $-distributions. The natural candidate for the large-$N$ limit of the empirical distribution…

Probability · Mathematics 2023-08-04 Bruce K. Driver , Brian C. Hall , Todd Kemp

The Lamperti transform offers a powerful bridge between self-similar processes and stationary dynamics, making it especially useful for analyzing anomalous diffusion models that lack stationary increments. In this paper we examine the…

Probability · Mathematics 2026-01-07 Foad Shokrollahi , Saeed Vahdati

In some non-regular statistical estimation problems, the limiting likelihood processes are functionals of fractional Brownian motion (fBm) with Hurst's parameter H; 0 < H <=? 1. In this paper we present several analytical and numerical…

Statistics Theory · Mathematics 2014-06-06 Alexander Novikov , Nino Kordzakhia , Timothy Ling

In this paper, we present several path properties, simulations, inferences, and generalizations of the weighted sub-fractional Brownian motion. A primary focus is on the derivation of the covariance function $R_{f,b}(s,t)$ for the weighted…

Probability · Mathematics 2024-09-10 Ramirez-Gonzalez Jose Hermenegildo , Sun Ying

Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model…

Data Analysis, Statistics and Probability · Physics 2015-02-06 Dave Higdon , Jordan D. McDonnell , Nicolas Schunck , Jason Sarich , Stefan M. Wild

Consider a Poisson point process with unknown support boundary curve $g$, which forms a prototype of an irregular statistical model. We address the problem of estimating non-linear functionals of the form $\int \Phi(g(x))\,dx$. Following a…

Statistics Theory · Mathematics 2019-02-13 Markus Reiß , Martin Wahl

This paper is concerned with nonlinear filtering of the coefficients in asset price models with stochastic volatility. More specifically, we assume that the asset price process $S=(S_{t})_{t\geq0}$ is given by \[ dS_{t}=m(\theta_{t})S_{t}…

Probability · Mathematics 2016-08-16 Jakša Cvitanić , Robert Liptser , Boris Rozovskii

In this paper, we consider a partially linear model of the form $Y_t=X_t^{\tau}\theta_0+g(V_t)+\epsilon_t$, $t=1,...,n$, where $\{V_t\}$ is a $\beta$ null recurrent Markov chain, $\{X_t\}$ is a sequence of either strictly stationary or…

Statistics Theory · Mathematics 2012-05-16 Jia Chen , Jiti Gao , Degui Li

Bayesian estimation is a vital tool in robotics as it allows systems to update the robot state belief using incomplete information from noisy sensors. To render the state estimation problem tractable, many systems assume that the motion and…

Robotics · Computer Science 2025-01-13 Miguel Saavedra-Ruiz , Steven A. Parkison , Ria Arora , James Richard Forbes , Liam Paull

A functional limit theorem for the empirical measure-valued process of eigenvalues of a matrix fractional Brownian motion is obtained. It is shown that the limiting measure-valued process is the non-commutative fractional Brownian motion…

Probability · Mathematics 2015-06-23 Juan Carlos Pardo , Victor Pérez-Abreu , José Luis Pérez-Garmendia

We give an asymptotic development of the maximum likelihood estimator (MLE), or any other estimator defined implicitly, in a way which involves the limiting behavior of the score and its higher-order derivatives. This development, which is…

Statistics Theory · Mathematics 2024-04-10 Antoine Lejay , Sara Mazzonetto

The Hartman-Watson distribution with density $f_r(t)$ is a probability distribution defined on $t \geq 0$ which appears in several problems of applied probability. The density of this distribution is expressed in terms of an integral…

Probability · Mathematics 2024-12-20 Dan Pirjol

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

We are interested in stochastic processes satisfying a nonlinear recurrence relation of the form $$X_{n + k} = \Phi_0 (X_n, ..., X_{n + k - 1}) + \Theta_n$$ where $\Theta$ is a noise term. We establish the existence of an invariant measure…

Dynamical Systems · Mathematics 2025-12-11 Lisette Jager , Killian Verdure

Suppose a process yields independent observations whose distributions belong to a family parameterized by \theta\in\Theta. When the process is in control, the observations are i.i.d. with a known parameter value \theta_0. When the process…

Statistics Theory · Mathematics 2007-06-13 Gary Lorden , Moshe Pollak

This paper is devoted to the synchronization of stochastic differential equations driven by the linear multiplicative fractional Brownian motion with Hurst parameter $H\in(\frac{1}{2},1)$. We firstly prove that the equation has a unique…

Probability · Mathematics 2023-12-12 Wei Wei , Hongjun Gao , Qiyong Cao

In this paper we consider the Stochastic isothermal, nonlinear, incompressible bipolar viscous fluids driven by a genuine cylindrical fractional Bronwnian motion with Hurst parameter $H \in (1/4,1/2)$ under Dirichlet boundary condition on…

Dynamical Systems · Mathematics 2011-12-24 Jin Li , Jianhua Huang

Consider the following stochastic differential equation for $(X_t)_{t\ge 0}$ on $\mathbb R^d$ and its Euler-Maruyama (EM) approximation $(Y_{t_n})_{n\in \mathbb Z^+}$: \begin{align*} &d X_t=b( X_t) d t+\sigma(X_t) d B_t, \\ &…

Probability · Mathematics 2023-10-03 Xiang Li , Feng-Yu Wang , Lihu Xu

We consider a combined state and drift estimation problem for the linear stochastic heat equation. The infinite-dimensional Bayesian inference problem is formulated in terms of the Kalman-Bucy filter over an extended state space, and its…

Statistics Theory · Mathematics 2020-08-18 Sebastian Reich , Paul Rozdeba
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