On nonparametric regression for bivariate circular long-memory time series
| Type of Publication: | Journal article |
| Publication status: | Published |
| URI (citable link): | http://nbn-resolving.de/urn:nbn:de:bsz:352-2-qyhrecwhqg129 |
| Author: | Beran, Jan; Steffens, Britta; Ghosh, Sucharita |
| Year of publication: | 2022 |
| Published in: | Statistical Papers ; 63 (2022), 1. - pp. 29-52. - 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 |
| Link to License: | Attribution 4.0 International |
| Bibliography of Konstanz: | Yes |
| Refereed: | Unknown |
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BERAN, Jan, Britta STEFFENS, Sucharita GHOSH, 2022. On nonparametric regression for bivariate circular long-memory time series. In: Statistical Papers. Springer. 63(1), pp. 29-52. ISSN 0932-5026. eISSN 1613-9798. Available under: doi: 10.1007/s00362-021-01228-1
@article{Beran2022-02nonpa-53410, title={On nonparametric regression for bivariate circular long-memory time series}, year={2022}, doi={10.1007/s00362-021-01228-1}, number={1}, volume={63}, issn={0932-5026}, journal={Statistical Papers}, pages={29--52}, author={Beran, Jan and Steffens, Britta and Ghosh, Sucharita} }
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