dc.contributor.authorHong, Zhaoping
dc.contributor.authorLian, Heng
dc.date.accessioned2013-10-31T03:52:39Z
dc.date.available2013-10-31T03:52:39Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationHong, Z., & Lian, H. (2012). Time-varying coefficient estimation in differential equation models with noisy time-varying covariates. Journal of multivariate analysis, 103(1), 58-67.en_US
dc.identifier.issn0047-259Xen_US
dc.identifier.urihttp://hdl.handle.net/10220/17116
dc.description.abstractWe study the problem of estimating time-varying coefficients in ordinary differential equations. Current theory only applies to the case when the associated state variables are observed without measurement errors as presented in Chen and Wu (2008) [4] and [5]. The difficulty arises from the quadratic functional of observations that one needs to deal with instead of the linear functional that appears when state variables contain no measurement errors. We derive the asymptotic bias and variance for the previously proposed two-step estimators using quadratic regression functional theory.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesJournal of multivariate analysisen_US
dc.subjectDRNTU::Science::Mathematics::Calculus
dc.titleTime-varying coefficient estimation in differential equation models with noisy time-varying covariatesen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.jmva.2011.06.007


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