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This paper studies the winding of a continuously differentiable Gaussian stationary process $f:\mathbb{R}\to\mathbb{C}$ in the interval $[0,T]$. We give formulae for the mean and the variance of this random variable. The variance is shown…

Probability · Mathematics 2016-06-30 Jeremiah Buckley , Naomi Feldheim

We introduce a model of self-propelled particles carrying out a Brownian motion with a diffusion coefficient which depends on the local density of particles within a certain finite radius. Numerical simulations show that in a range of…

Statistical Mechanics · Physics 2009-11-11 Cristobal Lopez

The paper deals with the regression model $X_t = \theta t + B_t$, $t\in[0, T ]$, where $B=\{B_t, t\geq 0\}$ is a centered Gaussian process with stationary increments. We study the estimation of the unknown parameter $\theta$ and establish…

Probability · Mathematics 2017-04-18 Yuliya Mishura , Kostiantyn Ralchenko , Sergiy Shklyar

We consider the problem of finding optimal strategies that maximize the average growth-rate of multiplicative stochastic processes. For a geometric Brownian motion the problem is solved through the so-called Kelly criterion, according to…

Portfolio Management · Quantitative Finance 2016-08-31 Francesco Caravelli , Lorenzo Sindoni , Fabio Caccioli , Cozmin Ududec

In this paper, we analyze Gaussian processes using statistical mechanics. Although the input is originally multidimensional, we simplify our model by considering the input as one-dimensional for statistical mechanical analysis. Furthermore,…

Statistical Mechanics · Physics 2025-05-05 Jun Tsuzurugi

The accurate prediction of time-changing variances is an important task in the modeling of financial data. Standard econometric models are often limited as they assume rigid functional relationships for the variances. Moreover, function…

Methodology · Statistics 2014-02-14 Yue Wu , Jose Miguel Hernandez Lobato , Zoubin Ghahramani

A simple variogram model with two parameters is presented that includes the power variogram for the fractional Brownian motion, a modified De Wijsian model, the generalized Cauchy model and the multiquadrics model. One parameter controls…

Methodology · Statistics 2014-12-08 Martin Schlather

Flip-flop processes refer to a family of stochastic fluid processes which converge to either a standard Brownian motion (SBM) or to a Markov modulated Brownian motion (MMBM). In recent years, it has been shown that complex distributional…

Probability · Mathematics 2021-10-12 Guy Latouche , Giang T. Nguyen , Oscar Peralta

We present a simple stochastic quadrant model for calculating the transport and de- position of heavy particles in a fully developed turbulent boundary layer based on the statistics of wall-normal fluid velocity fluctuations obtained from a…

Fluid Dynamics · Physics 2016-08-02 C. Jin , I. Potts , M. W. Reeks

We develop an exactly solvable framework of Markov decision process with a finite horizon, and continuous state and action spaces. We first review the exact solution of conventional linear quadratic regulation with a linear transition and a…

Machine Learning · Computer Science 2020-12-16 Yuan Yao , Xiaolin Sun

We perform a coarse-graining analysis of the paradigmatic active matter model, Active Brownian Particles, yielding a continuum description in terms of balance laws for mass, linear and angular momentum, and energy. The derivation of the…

Soft Condensed Matter · Physics 2019-04-30 Jeffrey M. Epstein , Katherine Klymko , Kranthi K. Mandadapu

The traction on the surface of a spherical active colloid in a thermally fluctuating Stokesian fluid contains passive, active, and Brownian contributions. Here we derive these three parts systematically, by "projecting out" the fluid using…

Soft Condensed Matter · Physics 2017-09-11 Rajesh Singh , R. Adhikari

"Quantum trajectories" are solutions of stochastic differential equations also called Belavkin or Stochastic Schr\"odinger Equations. They describe random phenomena in quantum measurement theory. Two types of such equations are usually…

Probability · Mathematics 2008-12-18 Clement Pellegrini

G-Brownian motion has a very rich and interesting new structure which nontrivially generalizes the classical one. Its quadratic variation process is also a continuous process with independent and stationary increments. We prove a…

Probability · Mathematics 2020-05-08 Li-Xin Zhang

We study a class of many body chaotic models related to the Brownian Sachdev-Ye-Kitaev model. An emergent symmetry maps the quantum dynamics into a classical stochastic process. Thus we are able to study many dynamical properties at finite…

Quantum Physics · Physics 2024-08-22 Shunyu Yao

In this paper we consider the drift estimation problem for a general differential equation driven by an additive multidimensional fractional Brownian motion, under ergodic assumptions on the drift coefficient. Our estimation procedure is…

Statistics Theory · Mathematics 2020-07-16 Fabien Panloup , Samy Tindel , Maylis Varvenne

A new type of nonstationary Gaussian process model is developed for approximating computationally expensive functions. The new model is a composite of two Gaussian processes, where the first one captures the smooth global trend and the…

Applications · Statistics 2013-01-14 Shan Ba , V. Roshan Joseph

In this paper a simple model for the evolution of the forward density of the future value of an asset is proposed. The model allows for a straightforward initial calibration to option prices and has dynamics that are consistent with…

Pricing of Securities · Quantitative Finance 2013-01-22 Henrik Hult , Filip Lindskog , Johan Nykvist

We describe all countable particle systems on $\mathbb{R}$ which have the following three properties: independence, Gaussianity and stationarity. More precisely, we consider particles on the real line starting at the points of a Poisson…

Probability · Mathematics 2010-11-16 Zakhar Kabluchko

We study the asymptotic behavior of estimators of a two-valued, discontinuous diffusion coefficient in a Stochastic Differential Equation, called an Oscillating Brownian Motion. Using the relation of the latter process with the Skew…

Probability · Mathematics 2017-01-10 Antoine Lejay , Paolo Pigato
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