Estimators of diffusions with randomly spaced discrete observations: A general theory

dc.creatorAit-Sahalia, Yacine
dc.creatorMykland, Per A.
dc.date2005-03-29
dc.date.accessioned2026-07-07T08:06:47Z
dc.date.available2026-07-07T08:06:47Z
dc.descriptionWe provide a general method to analyze the asymptotic properties of a variety of estimators of continuous time diffusion processes when the data are not only discretely sampled in time but the time separating successive observations may possibly be random. We introduce a new operator, the generalized infinitesimal generator, to obtain Taylor expansions of the asymptotic moments of the estimators. As a special case, our results apply to the situation where the data are discretely sampled at a fixed nonrandom time interval. We include as specific examples estimators based on maximum-likelihood and discrete approximations such as the Euler scheme.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053604000000427 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0503679
dc.identifierhttp://arxiv.org/abs/math/0503679
dc.identifierAnnals of Statistics 2004, Vol. 32, No. 5, 2186-2222
dc.identifierdoi:10.1214/009053604000000427
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130727
dc.subjectStatistics Theory
dc.subject62F12, 62M05 (Primary) 60H10, 60J60. (Secondary)
dc.titleEstimators of diffusions with randomly spaced discrete observations: A general theory
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