From Random Processes to Generalized Fields: A Unified Approach to Stochastic Integration

Simple item page
dc.creatorLototsky, S. V.
dc.creatorStemmann, K.
dc.date2007-06-16
dc.date.accessioned2026-07-07T08:10:38Z
dc.date.available2026-07-07T08:10:38Z
dc.descriptionThe paper studies stochastic integration with respect to Gaussian processes and fields. It is more convenient to work with a field than a process: by definition, a field is a collection of stochastic integrals for a class of deterministic integrands. The problem is then to extend the definition to random integrands. An orthogonal decomposition of chaos space of the random field leads to two such extensions, corresponding to the \Ito-Skorokhod and the Stratononovich integrals, and provides an efficient tool to study these integrals, both analytically and numerically. For a Gaussian process, a natural definition of the integral follows from a canonical correspondence between random processes and a special class of random fields.
dc.identifierhttps://arxiv.org/abs/0706.2391
dc.identifierhttp://arxiv.org/abs/0706.2391
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/131876
dc.subjectProbability
dc.subject60H05, 60G15, 60H07, 60H40
dc.titleFrom Random Processes to Generalized Fields: A Unified Approach to Stochastic Integration
dc.typetext

Files

Collections

arXiv