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We present a general framework for Bayesian estimation of incompletely observed multivariate diffusion processes. Observations are assumed to be discrete in time, noisy and incomplete. We assume the drift and diffusion coefficient depend on…

Methodology · Statistics 2019-02-04 Frank van der Meulen , Moritz Schauer

This paper is devoted to filtering, smoothing, and prediction of polynomial processes that are partially observed. These problems are known to allow for an explicit solution in the simpler case of linear Gaussian state space models. The key…

Probability · Mathematics 2025-07-10 Jan Kallsen , Ivo Richert

This paper deals with a comparison of Fractional Derivative and Monte carlo approaches to the modelling of anomalous diffusion in the field of particle transport. The goal of this research is to provide a better insight on the behavior of…

Statistical Mechanics · Physics 2007-06-15 M. Marseguerra , A. Zoia

Take a multidimensional normally or obliquely reflected diffusion in a smooth domain. Approximate it by solutions of stochastic differential equations without reflection using the penalty method. That is, we approximate the reflection term…

Probability · Mathematics 2021-08-09 Andrey Sarantsev

Several physics methods for the simulation of the photoelectric effect are quantitatively evaluated with respect to a large collection of experimental data retrieved from the literature. They include theoretical and empirical calculations…

When the unconditioned process is a diffusion submitted to a space-dependent killing rate $k(\vec x)$, various conditioning constraints can be imposed for a finite time horizon $T$. We first analyze the conditioned process when one imposes…

Statistical Mechanics · Physics 2022-09-01 Alain Mazzolo , Cécile Monthus

Modelling partial differential equations (PDEs) is of crucial importance in science and engineering, and it includes tasks ranging from forecasting to inverse problems, such as data assimilation. However, most previous numerical and machine…

This paper is concerned with the fractional evolution equation with a discrete distribution of Caputo time-derivatives such that the largest and the smallest orders, $\alpha$ and $\alpha_m$, satisfy the conditions $1<\alpha\le 2$ and…

Analysis of PDEs · Mathematics 2018-01-11 Emilia Bazhlekova , Ivan Bazhlekov

A class of discrete time random walks has recently been introduced to provide a stochastic process based numerical scheme for solving fractional order partial differential equations, including the fractional subdiffusion equation. Here we…

Numerical Analysis · Mathematics 2018-08-01 J. A. Nichols , B. I. Henry , C. N. Angstmann

Employing a classical density-functional description of liquid environments, we introduce a rigorous method for the diffusion quantum Monte Carlo calculation of free energies and thermodynamic averages of solvated systems that requires…

In a computer experiment the choice of suitable estimators to measure a physical quantity plays an important role. We propose a new direct route to determine estimators for observables which do not commute with the Hamiltonian. Our new…

Statistical Mechanics · Physics 2013-07-11 Riccardo Fantoni

There are various routes for deriving partial radial distribution functions of disordered systems from experimental diffraction (and/or EXAFS) data. Due to limitations and errors of experimental data, as well as to imperfections of the…

Disordered Systems and Neural Networks · Physics 2012-07-16 Z. Steinczinger , L. Pusztai

We propose nonparametric open-end sequential testing procedures that can detect all types of changes in the contemporary distribution function of possibly multivariate observations. Their asymptotic properties are theoretically investigated…

Methodology · Statistics 2022-11-15 Mark Holmes , Ivan Kojadinovic , Alex Verhoijsen

Closed-form stochastic filtering equations can be derived in a general setting where probability distributions are replaced by some specific outer measures. In this article, we study how the principles of the sequential Monte Carlo method…

Methodology · Statistics 2018-05-07 Jeremie Houssineau , Branko Ristic

Conditions preserving observability of specifications between the plant and its abstraction are essential for hierarchical supervisory control of discrete-event systems under partial observation. Observation consistency and local…

Systems and Control · Electrical Eng. & Systems 2023-02-27 Jan Komenda , Tomáš Masopust

This paper is concerned with differentiable resampling in the context of sequential Monte Carlo (e.g., particle filtering). Drawing on reparametrisation, we propose a new resampling method that is informative and instantly differentiable,…

Machine Learning · Statistics 2026-05-29 Jennifer Rosina Andersson , Zheng Zhao

We adapt the improved duality estimates for bounded coefficients derived by Canizo et al. to the framework of cross diffusion. Since the estimates can not be directly applied we need to derive a time discrete version of their results and…

Analysis of PDEs · Mathematics 2018-12-05 Thomas Lepoutre

The implementation and reliability of a quadratic diffusion Monte Carlo method for the study of ground-state properties of atoms are discussed. We show in the simple yet non-trivial calculation of the binding energy of the Li atom that the…

Condensed Matter · Physics 2009-11-07 A. Sarsa , J. Boronat , J. Casulleras

This paper derives physically meaningful boundary conditions for fractional diffusion equations, using a mass balance approach. Numerical solutions are presented, and theoretical properties are reviewed, including well-posedness and steady…

Analysis of PDEs · Mathematics 2017-06-27 Boris Baeumer , Mihály Kovács , Mark M. Meerschaert , Harish Sankaranarayanan

When permutation methods are used in practice, often a limited number of random permutations are used to decrease the computational burden. However, most theoretical literature assumes that the whole permutation group is used, and methods…

Statistics Theory · Mathematics 2018-08-20 Jesse Hemerik , Jelle Goeman