On aggregation of strongly dependent time series
Aufgrund von Vorbereitungen auf eine neue Version von KOPS, können kommenden Montag und Dienstag keine Publikationen eingereicht werden. (Due to preparations for a new version of KOPS, no publications can be submitted next Monday and Tuesday.)
| Type of Publication: | Journal article |
| Publication status: | Published |
| URI (citable link): | http://nbn-resolving.de/urn:nbn:de:bsz:352-2-14refwn3q4zha6 |
| Author: | Beran, Jan; Liu, Haiyan; Ghosh, Sucharita |
| Year of publication: | 2020 |
| Published in: | Scandinavian Journal of Statistics ; 47 (2020), 3. - pp. 690-710. - Wiley. - ISSN 0303-6898. - eISSN 1467-9469 |
| DOI (citable link): | https://dx.doi.org/10.1111/sjos.12421 |
| Summary: |
We consider cross‐sectional aggregation of time series with long‐range dependence. This question arises for instance from the statistical analysis of networks where aggregation is defined via routing matrices. Asymptotically, aggregation turns out to increase dependence substantially, transforming a hyperbolic decay of autocorrelations to a slowly varying rate. This effect has direct consequences for statistical inference. For instance, unusually slow rates of convergence for nonparametric trend estimators and nonstandard formulas for optimal bandwidths are obtained. The situation changes, when time‐dependent aggregation is applied. Suitably chosen time‐dependent aggregation schemes can preserve a hyperbolic rate or even eliminate autocorrelations completely.
|
| Subject (DDC): | 510 Mathematics |
| Link to License: | Attribution-NonCommercial-NoDerivatives 4.0 International |
| Bibliography of Konstanz: | Yes |
| Refereed: | Yes |
Cite This
Files in this item
![[PDF]](/themes/Kops/images/mimes/pdf.png "PDF file"){kind=small}
BERAN, Jan, Haiyan LIU, Sucharita GHOSH, 2020. On aggregation of strongly dependent time series. In: Scandinavian Journal of Statistics. Wiley. 47(3), pp. 690-710. ISSN 0303-6898. eISSN 1467-9469. Available under: doi: 10.1111/sjos.12421
@article{Beran2020-09aggre-48631, title={On aggregation of strongly dependent time series}, year={2020}, doi={10.1111/sjos.12421}, number={3}, volume={47}, issn={0303-6898}, journal={Scandinavian Journal of Statistics}, pages={690--710}, author={Beran, Jan and Liu, Haiyan and Ghosh, Sucharita} }
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/48631"> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-02-13T12:25:08Z</dcterms:available> <dc:contributor>Beran, Jan</dc:contributor> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/39"/> <dc:contributor>Liu, Haiyan</dc:contributor> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/48631/1/Beran_2-14refwn3q4zha6.pdf"/> <dc:language>eng</dc:language> <dcterms:title>On aggregation of strongly dependent time series</dcterms:title> <dc:rights>Attribution-NonCommercial-NoDerivatives 4.0 International</dc:rights> <dcterms:issued>2020-09</dcterms:issued> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/48631/1/Beran_2-14refwn3q4zha6.pdf"/> <dc:creator>Liu, Haiyan</dc:creator> <dc:creator>Beran, Jan</dc:creator> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-02-13T12:25:08Z</dc:date> <dc:contributor>Ghosh, Sucharita</dc:contributor> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/48631"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/39"/> <dc:creator>Ghosh, Sucharita</dc:creator> <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by-nc-nd/4.0/"/> <dcterms:abstract xml:lang="eng">We consider cross‐sectional aggregation of time series with long‐range dependence. This question arises for instance from the statistical analysis of networks where aggregation is defined via routing matrices. Asymptotically, aggregation turns out to increase dependence substantially, transforming a hyperbolic decay of autocorrelations to a slowly varying rate. This effect has direct consequences for statistical inference. For instance, unusually slow rates of convergence for nonparametric trend estimators and nonstandard formulas for optimal bandwidths are obtained. The situation changes, when time‐dependent aggregation is applied. Suitably chosen time‐dependent aggregation schemes can preserve a hyperbolic rate or even eliminate autocorrelations completely.</dcterms:abstract> </rdf:Description> </rdf:RDF>
Downloads since Feb 13, 2020 (Information about access statistics)
| Beran_2-14refwn3q4zha6.pdf | 119 |
This item appears in the following Collection(s)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International
Search KOPS
Browse
My Account
