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A subdiffusion problem in which the diffusion term is related to a stable stochastic process is introduced. Linear models of these systems have been studied in a general way, but non-linear models require a more specific analysis. The model…

Probability · Mathematics 2021-11-05 Soveny Solís , Vicente Vergara

We introduce Latent Gaussian Process Regression which is a latent variable extension allowing modelling of non-stationary multi-modal processes using GPs. The approach is built on extending the input space of a regression problem with a…

Machine Learning · Statistics 2017-09-19 Erik Bodin , Neill D. F. Campbell , Carl Henrik Ek

Christoffersen, Jacobs, Ornthanalai, and Wang (2008) (CJOW) proposed an improved Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model for valuing European options, where the return volatility is comprised of two distinct…

Econometrics · Economics 2024-10-21 Luca Vincenzo Ballestra , Enzo D'Innocenzo , Christian Tezza

A refracted L\'evy process is a L\'evy process whose dynamics change by subtracting off a fixed linear drift (of suitable size) whenever the aggregate process is above a pre-specified level. More precisely, whenever it exists, a refracted…

Probability · Mathematics 2012-05-04 Andreas E. Kyprianou , J. C. Pardo , J. L. Pérez

We study a stochastic model of protein dynamics that explicitly includes delay in the degradation. We rigorously derive the master equation for the processes and solve it exactly. We show that the equations for the mean values obtained…

Statistical Mechanics · Physics 2013-05-29 Luis F. Lafuerza , Raul Toral

We consider a stochastic functional delay differential equation, namely an equation whose evolution depends on its past history as well as on its present state, driven by a pure diffusive component plus a pure jump Poisson compensated…

Probability · Mathematics 2017-02-17 Francesco Cordoni , Luca Di Persio , Immacolata Oliva

A characteristic matrix function captures the spectral information of a bounded linear operator in a matrix-valued function. In this article, we consider a delay differential equation with one discrete time delay and assume this equation is…

Dynamical Systems · Mathematics 2022-01-31 Babette de Wolff

We present a novel extension of multi-output Gaussian processes for handling heterogeneous outputs. We assume that each output has its own likelihood function and use a vector-valued Gaussian process prior to jointly model the parameters in…

Machine Learning · Statistics 2019-01-04 Pablo Moreno-Muñoz , Antonio Artés-Rodríguez , Mauricio A. Álvarez

Ordinary differential equations of the second order with one constant delay are considered in this paper. An analytical representation of the solution is obtained using the method of steps.

Dynamical Systems · Mathematics 2014-04-29 Oleksandra Kukharenko

Let $X=\{X(t),t\in R_+\}$ be a real-valued symmetric L\'{e}vy process with continuous local times $\{L^x_t,(t,x)\in R_+\times R\}$ and characteristic function $Ee^{i\lambda X(t)}=e^{-t\psi(\lambda)}$. Let…

Probability · Mathematics 2009-09-29 Michael B. Marcus , Jay Rosen

Using generalized Blumenthal--Getoor indices, we obtain criteria for the finiteness of the $p$-variation of L\'evy-type processes. This class of stochastic processes includes solutions of Skorokhod-type stochastic differential equations…

Probability · Mathematics 2016-02-03 Martynas Manstavicius , Alexander Schnurr

We present an approach for testing for the existence of continuous generators of discrete stochastic transition matrices. Typically, the known approaches to ascertain the existence of continuous Markov processes are based in the assumption…

Data Analysis, Statistics and Probability · Physics 2016-03-23 Pedro Lencastre , Frank Raischel , Tim Rogers , Pedro G. Lind

Gated first-passage processes, where completion depends on both hitting a target and satisfying additional constraints, are prevalent across various fields. Despite their significance, analytical solutions to basic problems remain unknown,…

Statistical Mechanics · Physics 2024-09-04 Yuval Scher , Aanjaneya Kumar , M. S. Santhanam , Shlomi Reuveni

In this paper continuous time random walk models approximating fractional space-time diffusion processes are studied. Stochastic processes associated with the considered equations represent time-changed processes, where the time-change…

Probability · Mathematics 2014-09-16 Sabir Umarov

Range-measured return contains more information than the traditional scalar-valued return. In this paper, we propose to model the [low, high] price range as a random interval and suggest an interval-valued GARCH (Int-GARCH) model for the…

Methodology · Statistics 2019-01-11 Yan Sun , Guanghua Lian , Zudi Lu , Jennifer Loveland , Isaac Blackhurst

When considering the problem of forecasting a continuous-time stochastic process over an entire time-interval in terms of its recent past, the notion of Autoregressive Hilbert space processes (ARH) arises. This model can be seen as a…

Methodology · Statistics 2013-02-15 Jairo Cugliari

The generalized grey Brownian motion is a time continuous self-similar with stationary increments stochastic process whose one dimensional distributions are the fundamental solutions of a stretched time fractional differential equation.…

Probability · Mathematics 2021-01-01 José Luís da Silva , Mohamed Erraoui

In this paper, we investigate a class of stochastic impulsive fractional differential evolution equations with infinite delay in Banach space. Firstly sufficient conditions of the existence and uniqueness of the mild solution for this type…

Dynamical Systems · Mathematics 2015-08-10 Zhao Shufen , Song Minghui

Quantum graphs model processes in complex systems represented as spatial networks in various fields of natural science and technology. An example is the oscillations of elastic string networks, the nodes of which, besides the continuity…

Optimization and Control · Mathematics 2024-10-01 Sergey Buterin

When a spatial process is recorded over time and the observation at a given time instant is viewed as a point in a function space, the result is a time series taking values in a Banach space. To study the spatio-temporal extremal dynamics…

Probability · Mathematics 2010-01-20 Thomas Meinguet , Johan Segers