Estimation of stopping times for stopped self-similar random processes

Simple item page
dc.contributor.authorSchulmann, Viktor
dc.date.accessioned2021-06-07T05:57:17Z
dc.date.available2021-06-07T05:57:17Z
dc.date.issued2021-03-01
dc.description.abstractLet X=(Xt)t≥0 be a known process and T an unknown random time independent of X. Our goal is to derive the distribution of T based on an iid sample of XT. Belomestny and Schoenmakers (Stoch Process Appl 126(7):2092–2122, 2015) propose a solution based the Mellin transform in case where X is a Brownian motion. Applying their technique we construct a non-parametric estimator for the density of T for a self-similar one-dimensional process X. We calculate the minimax convergence rate of our estimator in some examples with a particular focus on Bessel processes where we also show asymptotic normality.en
dc.identifier.urihttp://hdl.handle.net/2003/40240
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-22113
dc.language.isoende
dc.relation.ispartofseriesStatistical inference for stochastic processes;24
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectEstimation of stopping timesen
dc.subjectMultiplicative deconvolutionen
dc.subjectMellin transformen
dc.subjectSelf-similar processen
dc.subjectBessel processen
dc.subject.ddc510
dc.titleEstimation of stopping times for stopped self-similar random processesen
dc.typeTextde
dc.type.publicationtypearticlede
dcterms.accessRightsopen access
eldorado.secondarypublicationtruede
eldorado.secondarypublication.primarycitationSchulmann, V. Estimation of stopping times for stopped self-similar random processes. Stat Inference Stoch Process 24, 477–498 (2021).de
eldorado.secondarypublication.primaryidentifierhttps://doi.org/10.1007/s11203-020-09234-0de

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Schulmann2021_Article_EstimationOfStoppingTimesForSt.pdf
Size:
621.16 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
4.85 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Lehrstuhl IV Stochastik und Analysis