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相关论文: Integration-by-Parts Characterizations of Gaussian…

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In this paper, using a very general Cameron--Storvick theorem on the Wiener space $C_0[0,T]$, we establish various integration by parts formulas involving generalized analytic Feynman integrals, generalized analytic Fourier--Feynman…

泛函分析 · 数学 2019-03-15 Seung Jun Chand , Jae Gil Choi

We introduce the notion of {\em covariance measure structure} for square integrable stochastic processes. We define Wiener integral, we develop a suitable formalism for stochastic calculus of variations and we make Gaussian assumptions only…

概率论 · 数学 2007-05-23 Ida Kruk , Francesco Russo , Ciprian Tudor

An integration by parts formula is the foundation for stochastic analysis on path spaces over a (finite dimensional) Riemannian manifold or over $R^n$, from which we may deduce the operator $d$ is closable and define the Laplacian operator…

概率论 · 数学 2019-11-25 K. D. Elworthy , Xue-Mei Li

The integration-by-parts formula discovered by Malliavin for the Ito map on Wiener space is proved using the two-parameter stochastic calculus. It is also shown that the solution of a one-parameter stochastic differential equation driven by…

概率论 · 数学 2009-03-24 J. R. Norris

By using the Malliavin calculus and finite jump approximations, the Driver-type integration by parts formula is established for the semigroup associated to stochastic (partial) differential equations with noises containing a subordinate…

概率论 · 数学 2016-01-11 Feng-Yu Wang

We establish an integration by parts formula in an abstract framework in order to study the regularity of the law for processes solution of stochastic differential equations with jumps, including equations with discontinuous coefficients…

概率论 · 数学 2012-09-14 Emmanuelle Clement , Vlad Bally

Gaussian processes are a versatile framework for learning unknown functions in a manner that permits one to utilize prior information about their properties. Although many different Gaussian process models are readily available when the…

This survey is a preliminary version of a chapter of the forthcoming book "Stochastic Analysis for Poisson Point Processes: Malliavin Calculus, Wiener-It\^o Chaos Expansions and Stochastic Geometry" edited by Giovanni Peccati and Matthias…

概率论 · 数学 2014-05-20 Günter Last

By using the Malliavin calculus and finite-jump approximations, the Driver-type integration by parts formula is established for the semigroup associated to stochastic differential equations with noises containing a subordinate Brownian…

概率论 · 数学 2013-08-28 Feng-Yu Wang

We construct surface measures in a Hilbert space endowed with a probability measure $\nu$. The theory fits for invariant measures of some stochastic partial differential equations such as Burgers and reaction--diffusion equations. Other…

概率论 · 数学 2016-08-23 Giuseppe Da Prato , Alessandra Lunardi , Luciano Tubaro

We consider random variables of the form $F=f(V_1,...,V_n)$, where $f$ is a smooth function and $V_i,i\in\mathbb{N}$, are random variables with absolutely continuous law $p_i(y) dy$. We assume that $p_i$, $i=1,...,n$, are piecewise…

概率论 · 数学 2007-05-23 Vlad Bally , Marie-Pierre Bavouzet , Marouen Messaoud

Stochastic integration \textit{wrt} Gaussian processes has raised strong interest in recent years, motivated in particular by its applications in Internet traffic modeling, biomedicine and finance. The aim of this work is to define and…

概率论 · 数学 2018-02-15 Joachim Lebovits

We show that every separable Gaussian process with integrable variance function admits a Fredholm representation with respect to a Brownian motion. We extend the Fredholm representation to a transfer principle and develop stochastic…

概率论 · 数学 2016-03-23 Tommi Sottinen , Lauri Viitasaari

Bayesian learning using Gaussian processes provides a foundational framework for making decisions in a manner that balances what is known with what could be learned by gathering data. In this dissertation, we develop techniques for…

机器学习 · 统计学 2022-04-29 Alexander Terenin

By using the Malliavin calculus, the Driver-type integration by parts formula is established for the semigroup associated to to SPDEs with Multiplicative Noise. Moreover, estimates on the density of heat kernel w.r.t. Lebesgue measure are…

概率论 · 数学 2016-10-11 Xing Huang , Shao-Qin Zhang , Li-Xia Liu

For a class of piecewise deterministic Markov processes we introduce a stochastic calculus which is a certain non-Gaussian counterpart to the classical Malliavin calculus. As an application we investigate the regularity of densities of…

概率论 · 数学 2023-06-21 Jörg-Uwe Löbus

In this paper we consider the nonparametric functional estimation of the drift of Gaussian processes using Paley-Wiener and Karhunen-Lo\`eve expansions. We construct efficient estimators for the drift of such processes, and prove their…

统计理论 · 数学 2018-08-20 Nicolas Privault , Anthony Reveillac

A strong quasi-invariance principle and a finite-dimensional integration by parts formula as in the Bismut approach to Malliavin calculus are obtained through a suitable application of Lie's symmetry theory to autonomous stochastic…

概率论 · 数学 2023-07-12 Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

In this article we study existence of pathwise stochastic integrals with respect to a general class of $n$-dimensional Gaussian processes and a wide class of adapted integrands. More precisely, we study integrands which are functions that…

概率论 · 数学 2014-11-25 Zhe Chen , Lauri Viitasaari

Integration by parts formulae are given for a class of measures on the space of paths of a smooth manifold $M$ determined by the laws of degenerate diffusions. The mother of such formulae, on the path space of diffeomorphism group of $M$ is…

概率论 · 数学 2019-11-25 K. D. Elworthy , Yves Le Jan , Xue-Mei Li
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