Smoothing ordered sparse contingency tables and the chi-2 test

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ABBERGER, Klaus, 2002. Smoothing ordered sparse contingency tables and the chi-2 test

@techreport{Abberger2002Smoot-11780, series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie}, title={Smoothing ordered sparse contingency tables and the chi-2 test}, year={2002}, number={2002/09}, author={Abberger, Klaus} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dcterms:rights rdf:resource=""/> <dcterms:available rdf:datatype="">2011-03-25T09:40:13Z</dcterms:available> <dcterms:hasPart rdf:resource=""/> <dcterms:title>Smoothing ordered sparse contingency tables and the chi-2 test</dcterms:title> <dc:format>application/pdf</dc:format> <dcterms:issued>2002</dcterms:issued> <dc:language>eng</dc:language> <dc:date rdf:datatype="">2011-03-25T09:40:13Z</dc:date> <dspace:hasBitstream rdf:resource=""/> <dc:rights>terms-of-use</dc:rights> <dc:contributor>Abberger, Klaus</dc:contributor> <dcterms:abstract xml:lang="eng">To estimate cell probabilities for ordered sparse contingency tables several smooth- ing techniques have been investigated. It has been recognized that nonparamet- ric smoothing methods provide estimators of cell probabilities that have better performance than the pure frequency estimators. With the help of simulation examples it is shown in this paper that these smoothing techniques may help to get test which are more powerful than chi-2 test with raw data. But the distribution of the chi-2 statistics after smoothing is unknown. This distribution can also be estimated by simulation methods.</dcterms:abstract> <dspace:isPartOfCollection rdf:resource=""/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <bibo:uri rdf:resource=""/> <dc:creator>Abberger, Klaus</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dcterms:isPartOf rdf:resource=""/> </rdf:Description> </rdf:RDF>

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