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Observations which are realizations from some continuous process are frequent in sciences, engineering, economics, and other fields. We consider linear models, with possible random effects, where the responses are random functions in a…

Statistics Theory · Mathematics 2016-11-30 Giacomo Aletti , Caterina May , Chiara Tommasi

We consider additive functionals of stationary Markov processes and show that under Kipnis-Varadhan type conditions they converge in rough path topology to a Stratonovich Brownian motion, with a correction to the Levy area that can be…

Probability · Mathematics 2019-12-23 Jean-Dominique Deuschel , Tal Orenshtein , Nicolas Perkowski

Marginal structural models were introduced in order to provide estimates of causal effects from interventions based on observational studies in epidemiological research. The key point is that this can be understood in terms of Girsanov's…

Statistics Theory · Mathematics 2011-07-15 Kjetil Røysland

Mathematical models are sometime given as functions of independent input variables and equations or inequations connecting the input variables. A probabilistic characterization of such models results in treating them as functions with…

Optimization and Control · Mathematics 2023-04-13 Matieyendou Lamboni

We express the probabilistic character associated to the wave function by treating it as a stochastic variable. This is accomplished by means of a stochastic equation for the wave function whose noise changes the phase of the wave function…

Quantum Physics · Physics 2026-01-08 Mário J. de Oliveira

By using a simple observation that the density processes appearing in Ito's martingale representation theorem are invariant under the change of measures, we establish a non-linear version of the Cameron-Martin formula for solutions of a…

Probability · Mathematics 2010-11-16 G. Liang , A. Lionnet , Z. Qian

Partition functions of probability distributions are important quantities for model evaluation and comparisons. We present a new method to compute partition functions of complex and multimodal distributions. Such distributions are often…

Machine Learning · Statistics 2016-05-27 David Carlson , Patrick Stinson , Ari Pakman , Liam Paninski

We consider the ratio of two Gauss hypergeometric functions, in which the parameters of the numerator function differ from the respective parameters of the denominator function by integers. We derive explicit integral representations for…

Classical Analysis and ODEs · Mathematics 2021-12-30 Alexander Dyachenko , Dmitrii Karp

We construct planar semimartingales that include the Walsh Brownian motion as a special case, and derive Harrison-Shepp-type equations and a change-of-variable formula in the spirit of Freidlin-Sheu for these so-called "Walsh…

Probability · Mathematics 2016-03-01 Tomoyuki Ichiba , Ioannis Karatzas , Vilmos Prokaj , Minghan Yan

We establish a new scale of $p$-variation estimates for martingale paraproducts, martingale transforms, and It\^o integrals, of relevance in rough paths theory, stochastic, and harmonic analysis. As an application, we introduce rough…

Probability · Mathematics 2023-03-22 Peter Friz , Pavel Zorin-Kranich

We develop a compositional approach for automatic and symbolic differentiation based on categorical constructions in functional analysis where derivatives are linear functions on abstract vectors rather than being limited to scalars,…

Programming Languages · Computer Science 2022-07-05 Martin Elsman , Fritz Henglein , Robin Kaarsgaard , Mikkel Kragh Mathiesen , Robert Schenck

We give a bare-hands approach to the martingale representation theorem for integer valued random measures, which allows for a wide class of infinite activity jump processes, as well as all processes with well-ordered jumps.

Probability · Mathematics 2013-10-24 Samuel N. Cohen

For a real Borel measurable function b, which satisfies certain integrability conditions, it is possible to define a stochastic integral of the process b(Y) with respect to a Brownian motion W, where Y is a diffusion driven by W. It is well…

Probability · Mathematics 2010-10-06 Aleksandar Mijatović , Nika Novak , Mikhail Urusov

We work in the setting of the progressive enlargement $\mathbb G$ of a reference filtration $\mathbb F$ through the observation of a random time $\tau$. We study an integral representation property for some classes of $\mathbb…

Probability · Mathematics 2018-08-14 Anna Aksamit , Monique Jeanblanc , Marek Rutkowski

In this paper, we study integral functionals defined on spaces of functions with values on general (non-separable) Banach spaces. We introduce a new class of integrands and multifunctions for which we obtain measurable selection results.…

Optimization and Control · Mathematics 2022-08-10 Juan Guillermo Garrido , Pedro Pérez-Aros , Emilio Vilches

In this article, we study predictable projections of stochastic integrals with respect to the conformal Brownian motion, extending the connection between powers of the conformal Brownian motion and the corresponding Hermite polynomials. As…

Probability · Mathematics 2012-03-16 Matteo Casserini , Freddy Delbaen

Multifractal scaling has been extensively studied for real-valued stochastic processes, but a systematic integer-valued analogue has remained largely unexplored. In this work, we introduce a multifractal framework for integer-valued…

Probability · Mathematics 2025-09-29 Danijel Grahovac

In this paper, we obtain explicit product and moment formulas for products of iterated integrals generated by families of square integrable martingales associated with an arbitrary L\'evy process. We propose a new approach applying the…

Probability · Mathematics 2018-09-04 Paolo Di Tella , Christel Geiss

This paper assumes a robust stochastic model where a set $\mathcal{P}$ of probability measures replaces the single probability measure of dominated models. We introduce and study $\mathcal{P}$-sensitive functions defined on robust function…

Probability · Mathematics 2026-01-28 Johannes Langner , Gregor Svindland

Variational integrators are derived for structure-preserving simulation of stochastic forced Hamiltonian systems. The derivation is based on a stochastic discrete Hamiltonian which approximates a type-II stochastic generating function for…

Numerical Analysis · Mathematics 2020-02-07 Michael Kraus , Tomasz M. Tyranowski