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This paper proposes new parametric model adequacy tests for possibly nonlinear and nonstationary time series models with noncontinuous data distribution, which is often the case in applied work. In particular, we consider the correct…

Statistics Theory · Mathematics 2021-08-10 Igor Kheifets , Carlos Velasco

We study an irreversible Markov chain Monte Carlo method based on a skew detailed balance condition for an one-dimensional Ising model. Dynamical behavior of the magnetization density is analyzed in order to understand the properties of…

Statistical Mechanics · Physics 2015-06-12 Yuji Sakai , Koji Hukushima

We model the performance of an ideal closed chain of L processing elements that work in parallel in an asynchronous manner. Their state updates follow a generic conservative algorithm. The conservative update rule determines the growth of a…

Condensed Matter · Physics 2007-05-23 A. Kolakowska , M. A. Novotny , Per Arne Rikvold

Construction projects frequently experience schedule delays and forecasting uncertainty due to variability in labor productivity, material availability, weather conditions, and project coordination. Conventional deterministic scheduling…

Computational Engineering, Finance, and Science · Computer Science 2026-05-19 Atena Khoshkonesh , Mohsen Mohammadagha , Vinayak Kaushal , Navid Ebrahimi

We provide a compact derivation of the static and dynamic equations for infinite-dimensional particle systems in the liquid and glass phases. The static derivation is based on the introduction of an "auxiliary" disorder and the use of the…

Statistical Mechanics · Physics 2016-03-23 Jorge Kurchan , Thibaud Maimbourg , Francesco Zamponi

In this paper we establish the convergence of a numerical scheme based, on the Finite Element Method, for a time-independent problem modelling the deformation of a linearly elastic elliptic membrane shell subjected to remaining confined in…

Analysis of PDEs · Mathematics 2023-10-25 Aaron Meixner , Paolo Piersanti

A novel class of non-reversible Markov chain Monte Carlo schemes relying on continuous-time piecewise-deterministic Markov Processes has recently emerged. In these algorithms, the state of the Markov process evolves according to a…

Methodology · Statistics 2018-05-16 Paul Vanetti , Alexandre Bouchard-Côté , George Deligiannidis , Arnaud Doucet

The numerical realization of the dynamic programming principle for continuous-time optimal control leads to nonlinear Hamilton-Jacobi-Bellman equations which require the minimization of a nonlinear mapping over the set of admissible…

Optimization and Control · Mathematics 2015-02-26 Dante Kalise , Axel Kröner , Karl Kunisch

Current molecular dynamic simulations of biomolecules using multiple time steps to update the slowingly changing force are hampered by an instability occuring at time step equal to half the period of the fastest vibrating mode. This has…

Chemical Physics · Physics 2009-11-10 Siu A. Chin

Hyperbolic balance laws with uncertain (random) parameters and inputs are ubiquitous in science and engineering. Quantification of uncertainty in predictions derived from such laws, and reduction of predictive uncertainty via data…

Statistics Theory · Mathematics 2021-04-28 Francesca Boso , Daniel M. Tartakovsky

The classical Ka\v{c}anov scheme for the solution of nonlinear variational problems can be interpreted as a fixed point iteration method that updates a given approximation by solving a linear problem in each step. Based on this observation,…

Numerical Analysis · Mathematics 2021-11-30 Pascal Heid , Thomas P. Wihler

A Bayesian data assimilation scheme is formulated for advection-dominated or hyperbolic evolutionary problems, and observations. The method is referred to as the dynamic likelihood filter because it exploits the model physics to dynamically…

Dynamical Systems · Mathematics 2017-04-26 Juan M. Restrepo

Parallel replica dynamics is a method for accelerating the computation of processes characterized by a sequence of infrequent events. In this work, the processes are governed by the overdamped Langevin equation. Such processes spend much of…

Numerical Analysis · Mathematics 2012-09-04 Gideon Simpson , Mitchell Luskin

Robust Markov decision processes (MDPs) aim to handle changing or partially known system dynamics. To solve them, one typically resorts to robust optimization methods. However, this significantly increases computational complexity and…

Machine Learning · Computer Science 2021-10-14 Esther Derman , Matthieu Geist , Shie Mannor

Statistical calibration where the curve is nonlinear is important in many areas, such as analytical chemistry and radiometry. Especially in radiometry, instrument characteristics change over time, thus calibration is a process that must be…

Applications · Statistics 2014-11-14 Derick L. Rivers , Edward L. Boone

We study the stochastic dynamics of Ising spin models with random bonds, interacting on finitely connected Poissonnian random graphs. We use the dynamical replica method to derive closed dynamical equations for the joint spin-field…

Disordered Systems and Neural Networks · Physics 2009-11-13 A. Mozeika , A. C. C. Coolen

Inspired by the idea of stochastic quantization proposed by Parisi and Wu, we construct the transition probability matrix which plays a central role in the renormalization group through a stochastic differential equation. By establishing…

Probability · Mathematics 2022-10-13 Kaiyuan Cui , Fuzhou Gong

We present a mathematical approach that simplifies the theoretical treatment of electromagnetic localization in random media and leads to closed form analytical solutions. Starting with the assumption that the dielectric permittivity of the…

Optics · Physics 2009-11-13 Dimitris Dimitropoulos , Bahram Jalali

Combining dynamic renormalization with equation-free computational tools, we study the apparently self-similar evolution of void distribution dynamics in the diffusion-deposition problem proposed by Stinchcombe and Depken [Phys. Rev. Lett.…

Soft Condensed Matter · Physics 2007-05-23 L. Chen , I. G. Kevrekidis , P. G. Kevrekidis

Continuous data assimilation addresses time-dependent problems with unknown initial conditions by incorporating observations of the solution into a nudging term. For the prototypical heat equation with variable conductivity and the Neumann…

Numerical Analysis · Mathematics 2025-04-01 Vladimir Yushutin
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