Publikation: Iterative plug-in algorithms for SEMIFAR models : definition, convergence and asymptotic properties
Lade...
Dateien
Datum
2001
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Working Paper/Technical Report
Publikationsstatus
Published
Erschienen in
Zusammenfassung
In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparamet ric trend and maximum likelihood estimation of the parameters. Convergence and asymptotic properties of the proposed algorithms are investigated. A large simulation study illustrates the practical performance of the methods.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
330 Wirtschaft
Schlagwörter
semiparametric models, long-range dependence, fractional ARIMA, antipersistence, nonparametric regression, bandwidth selection
Konferenz
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690
BERAN, Jan, Yuanhua FENG, 2001. Iterative plug-in algorithms for SEMIFAR models : definition, convergence and asymptotic propertiesBibTex
@techreport{Beran2001Itera-668,
year={2001},
series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie},
title={Iterative plug-in algorithms for SEMIFAR models : definition, convergence and asymptotic properties},
number={2001/11},
author={Beran, Jan and Feng, Yuanhua}
}RDF
<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/server/rdf/resource/123456789/668">
<bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/668"/>
<dc:contributor>Beran, Jan</dc:contributor>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-22T17:45:26Z</dc:date>
<dc:rights>terms-of-use</dc:rights>
<dc:creator>Beran, Jan</dc:creator>
<dcterms:abstract xml:lang="eng">In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparamet ric trend and maximum likelihood estimation of the parameters. Convergence and asymptotic properties of the proposed algorithms are investigated. A large simulation study illustrates the practical performance of the methods.</dcterms:abstract>
<dcterms:title>Iterative plug-in algorithms for SEMIFAR models : definition, convergence and asymptotic properties</dcterms:title>
<dc:format>application/pdf</dc:format>
<dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
<dc:contributor>Feng, Yuanhua</dc:contributor>
<dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/668/1/dp0111.pdf"/>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/>
<dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/668/1/dp0111.pdf"/>
<dc:creator>Feng, Yuanhua</dc:creator>
<dc:language>eng</dc:language>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-22T17:45:26Z</dcterms:available>
<dcterms:issued>2001</dcterms:issued>
</rdf:Description>
</rdf:RDF>Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
