Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Woerner, Jeannette | - |
dc.contributor.author | Hufnagel, Nicole | - |
dc.date.accessioned | 2023-02-14T11:37:26Z | - |
dc.date.available | 2023-02-14T11:37:26Z | - |
dc.date.issued | 2021-08-04 | - |
dc.identifier.uri | http://hdl.handle.net/2003/41236 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-23080 | - |
dc.description.abstract | In this paper we derive martingale estimating functions for the dimensionality parameter of a Bessel process based on the eigenfunctions of the diffusion operator. Since a Bessel process is non-ergodic and the theory of martingale estimating functions is developed for ergodic diffusions, we use the space-time transformation of the Bessel process and formulate our results for a modified Bessel process. We deduce consistency, asymptotic normality and discuss optimality. It turns out that the martingale estimating function based of the first eigenfunction of the modified Bessel process coincides with the linear martingale estimating function for the Cox Ingersoll Ross process. Furthermore, our results may also be applied to estimating the multiplicity parameter of a one-dimensional Dunkl process and some related polynomial processes. | en |
dc.language.iso | en | de |
dc.relation.ispartofseries | Statistical inference for stochastic processes;Vol. 25. 2022, Issue 2, pp 337–353 | - |
dc.subject | Bessel process | en |
dc.subject | Non-ergodic diffusion | en |
dc.subject | Martingale estimating function | en |
dc.subject | Eigenfunctions | en |
dc.subject.ddc | 510 | - |
dc.title | Martingale estimation functions for Bessel processes | en |
dc.type | Text | de |
dc.type.publicationtype | article | de |
dcterms.accessRights | open access | - |
eldorado.secondarypublication | true | de |
eldorado.secondarypublication.primaryidentifier | https://doi.org/10.1007/s11203-021-09250-8 | de |
eldorado.secondarypublication.primarycitation | Statistical inference for stochastic processes. Vol. 25. 2022, Issue 2, pp 337-353 | de |
Appears in Collections: | Lehrstuhl IV Stochastik und Analysis |
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s11203-021-09250-8.pdf | 298.75 kB | Adobe PDF | View/Open |
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