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In this paper we consider a variety of procedures for numerical statistical inference in the family of univariate and multivariate stable distributions. In connection with univariate distributions (i) we provide approximations by finite…

Computation · Statistics 2012-09-04 Efthymios G. Tsionas

We present a simulation scheme for discrete-velocity gases based on {\em local thermodynamic equilibrium}. Exploiting the kinetic nature of discrete-velocity gases, in that context, results in a natural splitting of fluxes, and the…

comp-gas · Physics 2008-02-03 Balu Nadiga , Dale Pullin

We propose a new method for the determination of the weight factor for the simulated tempering method. In this method a short replica-exchange simulation is performed and the simulated tempering weight factor is obtained by the…

Statistical Mechanics · Physics 2009-10-31 A. Mitsutake , Y. Okamoto

We consider dynamical systems evolving near an equilibrium statistical state where the interest is in modelling long term behavior that is consistent with thermodynamic constraints. We adjust the distribution using an entropy-optimizing…

Fluid Dynamics · Physics 2014-11-25 Keith Myerscough , Jason Frank , Benedict Leimkuhler

Stochastic diffusion equations are crucial for modeling a range of physical phenomena influenced by uncertainties. We introduce the generalized finite difference method for solving these equations. Then, we examine its consistency,…

Numerical Analysis · Mathematics 2024-11-22 Faezeh Nassajian Mojarrad

Uncertainty propagation in non-linear dynamical systems has become a key problem in various fields including control theory and machine learning. In this work we focus on discrete-time non-linear stochastic dynamical systems. We present a…

Systems and Control · Electrical Eng. & Systems 2024-09-12 Eduardo Figueiredo , Andrea Patane , Morteza Lahijanian , Luca Laurenti

Models of complex dynamical systems like the Earth's climate often involve large numbers of uncertain parameters. Comprehensive exploration of the parameter space is typically prohibitive due to excessive computational costs. Systematic…

Atmospheric and Oceanic Physics · Physics 2026-03-27 Daniel Pals , Sebastian Bathiany , Richard Wood , Joel Kuettel , Niklas Boers

In this paper we derive stochastic representations for the finite dimensional distributions of a multidimensional diffusion on a fixed time interval, conditioned on the terminal state. The conditioning can be with respect to a fixed point…

Probability · Mathematics 2014-07-29 Christian Bayer , John Schoenmakers

We study numerical methods for dissipative particle dynamics (DPD), which is a system of stochastic differential equations and a popular stochastic momentum-conserving thermostat for simulating complex hydrodynamic behavior at mesoscales.…

Numerical Analysis · Mathematics 2021-06-08 Xiaocheng Shang

This letter studies a distribution-free, finite-sample data perturbation (DP) method, the Residual-Permuted Sums (RPS), which is an alternative of the Sign-Perturbed Sums (SPS) algorithm, to construct confidence regions. While SPS assumes…

Systems and Control · Electrical Eng. & Systems 2024-06-11 Szabolcs Szentpéteri , Balázs Csanád Csáji

For an unknown continuous distribution on a real line, we consider the approximate estimation by the discretization. There are two methods for the discretization. First method is to divide the real line into several intervals before taking…

Statistics Theory · Mathematics 2017-10-12 Yo Sheena

The ability to construct a realistic simulator of financial exchanges, including reproducing the dynamics of the limit order book, can give insight into many counterfactual scenarios, such as a flash crash, a margin call, or changes in…

Machine Learning · Computer Science 2023-11-28 Namid R. Stillman , Rory Baggott , Justin Lyon , Jianfei Zhang , Dingqiu Zhu , Tao Chen , Perukrishnen Vytelingum

Mixture distributions arise in many application areas, for example as marginal distributions or convolutions of distributions. We present a method of constructing an easily tractable discrete mixture distribution as an approximation to a…

Computation · Statistics 2017-02-20 Christian Röver , Tim Friede

We use simulation to estimate the steady-state performance of a stable multiclass queueing network. Standard estimators have been seen to perform poorly when the network is heavily loaded. We introduce two new simulation estimators. The…

Probability · Mathematics 2020-05-29 Shane G. Henderson , Sean P. Meyn

In this paper, we provide for the first time an automated, correct-by-construction, controller synthesis scheme for a class of infinite dimensional stochastic systems, namely, retarded jump-diffusion systems. First, we construct finite…

Optimization and Control · Mathematics 2019-11-22 Pushpak Jagtap , Majid Zamani

Temporal data distribution shift is prevalent in the financial text. How can a financial sentiment analysis system be trained in a volatile market environment that can accurately infer sentiment and be robust to temporal data distribution…

Computation and Language · Computer Science 2023-10-20 Yue Guo , Chenxi Hu , Yi Yang

The evolution of a continuous time Markov process with a finite number of states is usually calculated by the Master equation - a linear differential equations with a singular generator matrix. We derive a general method for reducing the…

Quantitative Methods · Quantitative Biology 2012-07-19 Daniel Soudry , Ron Meir

Building upon recent developments of force-based estimators with a reduced variance for the computation of densities, radial distribution functions or local transport properties from molecular simulations, we show that the variance can be…

Chemical Physics · Physics 2021-05-18 Samuel W. Coles , Etienne Mangaud , Daan Frenkel , Benjamin Rotenberg

The simulated tempering (ST) is an important method to deal with systems whose phase spaces are hard to sample ergodically. However, it uses accepting probabilities weights which often demand involving and time consuming calculations. Here…

Statistical Mechanics · Physics 2015-05-20 Carlos E. Fiore , M. G. E. da Luz

We introduce iterative tilting, a gradient-free method for fine-tuning diffusion models toward reward-tilted distributions. The method decomposes a large reward tilt $\exp(\lambda r)$ into $N$ sequential smaller tilts, each admitting a…

Machine Learning · Statistics 2025-12-04 Jean Pachebat , Giovanni Conforti , Alain Durmus , Yazid Janati