On nonparametric regression for bivariate circular long-memory time series
| Type of Publication: | Journal article |
| Publication status: | Published |
| Author: | Beran, Jan; Steffens, Britta; Ghosh, Sucharita |
| Year of publication: | 2021 |
| Published in: | Statistical Papers ; 2021. - Springer. - ISSN 0932-5026. - eISSN 1613-9798 |
| DOI (citable link): | https://dx.doi.org/10.1007/s00362-021-01228-1 |
| Summary: |
We consider nonparametric regression for bivariate circular time series with long-range dependence. Asymptotic results for circular Nadaraya–Watson estimators are derived. Due to long-range dependence, a range of asymptotically optimal bandwidths can be found where the asymptotic rate of convergence does not depend on the bandwidth. The result can be used for obtaining simple confidence bands for the regression function. The method is illustrated by an application to wind direction data.
|
| Subject (DDC): | 510 Mathematics |
| Bibliography of Konstanz: | Yes |
| Refereed: | Unknown |
| Online First: Journal articles that are published online before they appear as an actual part of a journal issue. Online first articles are published on the journal's website in the publisher's version. | |
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BERAN, Jan, Britta STEFFENS, Sucharita GHOSH, 2021. On nonparametric regression for bivariate circular long-memory time series. In: Statistical Papers. Springer. ISSN 0932-5026. eISSN 1613-9798. Available under: doi: 10.1007/s00362-021-01228-1
@article{Beran2021-03-20nonpa-53410, title={On nonparametric regression for bivariate circular long-memory time series}, year={2021}, doi={10.1007/s00362-021-01228-1}, issn={0932-5026}, journal={Statistical Papers}, author={Beran, Jan and Steffens, Britta and Ghosh, Sucharita} }
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Except where otherwise noted, this item's license is described as Attribution 4.0 International
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