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We give a theory of sublinear expectations and martingales in discrete time. Without assuming the existence of a dominating probability measure, we derive the extensions of classical results on uniform integrability, optional stopping of…

Probability · Mathematics 2011-04-29 Samuel Cohen , Shaolin Ji , Shige Peng

The effective, fast transport of matter through porous media is often characterized by complex dispersion effects. To describe in mathematical terms such situations, instead of a simple macroscopic equation (as in the classical Darcy's…

Numerical Analysis · Mathematics 2025-05-06 Surendra Nepal , Vishnu Raveendran , Michael Eden , Rainey Lyons , Adrian Muntean

We study the existence of the product of two weighted modulation spaces. For this purpose we discuss two different strategies. The more simple one allows transparent proofs in various situations. However, our second method allows a closer…

Functional Analysis · Mathematics 2016-02-02 Maximilian Reich , Winfried Sickel

Starting from elementary considerations about independence and Markov processes in classical probability we arrive at the new concept of conditional monotone independence (or operator-valued monotone independence). With the help of product…

Operator Algebras · Mathematics 2007-05-23 Michael Skeide

We examine when differentially flat nonlinear control systems with more than two inputs can be rendered static feedback linearizable by a minimal number of prolongations of suitably chosen inputs after applying a static input…

Dynamical Systems · Mathematics 2026-04-06 Georg Hartl , Conrad Gstöttner , Markus Schöberl

This paper is concerned with the detection of multiple change-points in the joint distribution of independent categorical variables. The procedures introduced rely on model selection and are based on a penalized least-squares criterion.…

Statistics Theory · Mathematics 2008-01-08 Nathalie Akakpo

Stochastic solutions provide new rigorous results for nonlinear PDE's and, through its local non-grid nature, are a natural tool for parallel computation. There are two different approaches for the construction of stochastic solutions:…

Mathematical Physics · Physics 2012-09-17 Rui Vilela Mendes

The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. This problem is very important in applications but there is no systematic study of it. We present here a new technique, which…

Numerical Analysis · Mathematics 2017-03-13 V. N. Temlyakov

In [Schuhmacher, Electron. J. Probab. 10 (2005), 165--201] estimates of the Barbour-Brown distance d_2 between the distribution of a thinned point process and the distribution of a Poisson process were derived by combining discretization…

Probability · Mathematics 2007-05-23 Dominic Schuhmacher

We provide two methods to construct zero-range processes with superlinear rates on ${\mathbb Z}^d$. In the first method these rates can grow very fast, if either the dynamics and the initial distribution are translation invariant or if only…

Probability · Mathematics 2021-05-11 Enrique Andjel , Inés Armendáriz , Milton Jara

This paper presents a Bayesian generative model for dependent Cox point processes, alongside an efficient inference scheme which scales as if the point processes were modelled independently. We can handle missing data naturally, infer…

Machine Learning · Statistics 2014-07-28 Tom Gunter , Chris Lloyd , Michael A. Osborne , Stephen J. Roberts

This paper presents two explicit Model Predictive Control formulations for linear systems parameterized in terms of design variables. Such parameter dependent behavior commonly arises from operating point dependent linearization of…

Systems and Control · Electrical Eng. & Systems 2026-04-02 Carlos J. G. Rojas , Esteban Lage Cano , Leyla Özkan

In this paper we propose a new method of estimation for discrete choice demand models when individual level data are available. The method employs a two-step procedure. Step 1 predicts the choice probabilities as functions of the observed…

Applications · Statistics 2020-10-19 Nick Doudchenko , Evgeni Drynkin

New algorithms for construction of asymptotic expansions for stationary distributions of nonlinearly perturbed semi-Markov processes with finite phase spaces are presented. These algorithms are based on a special technique of sequential…

Probability · Mathematics 2016-03-16 Dmitrii Silvestrov , Sergei Silvestrov

A spatial point process can be characterized by an intensity function which predicts the number of events that occur across space. In this paper, we develop a method to infer predictive intensity intervals by learning a spatial model using…

Machine Learning · Statistics 2020-07-06 Muhammad Osama , Dave Zachariah , Petre Stoica

We solve two continuous extremal problems on the classes of monotone functions: in the first problem we find extremal values for a line integral of a coordinate-wise monotone function of two variables from a rearrange\-ment-invariant class…

Functional Analysis · Mathematics 2026-03-03 Oleg Kovalenko

The solution of the continuous time filtering problem can be represented as a ratio of two expectations of certain functionals of the signal process that are parametrized by the observation path. We introduce a new time discretisation of…

Probability · Mathematics 2014-08-26 Dan Crisan , Salvador Ortiz-Latorre

In this paper a new dissimilarity measure to identify groups of assets dynamics is proposed. The underlying generating process is assumed to be a diffusion process solution of stochastic differential equations and observed at discrete time.…

Statistical Finance · Quantitative Finance 2008-12-02 Alessandro De Gregorio , Stefano Maria Iacus

Convergence of a full discretization of a second order stochastic evolution equation with nonlinear damping is shown and thus existence of a solution is established. The discretization scheme combines an implicit time stepping scheme with…

Probability · Mathematics 2016-10-12 Etienne Emmrich , David Šiška

In stochastic decision problems, one often wants to estimate the underlying probability measure statistically, and then to use this estimate as a basis for decisions. We shall consider how the uncertainty in this estimation can be…

Statistics Theory · Mathematics 2017-05-24 Samuel N. Cohen
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