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The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates

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Published in:Econometrics
Format: Online Article RSS Article
Published: 2023
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container_title Econometrics
description
discipline_display Natural Sciences
discipline_facet Natural Sciences
format Online Article
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institution FRELIP
journal_source_facet Econometrics
publishDate 2023
publishDateSort 2023
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spellingShingle The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates
Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
sub_discipline_display Natural Sciences — Mathematical Sciences
sub_discipline_facet Natural Sciences — Mathematical Sciences
subject_display Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
subject_facet Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
title The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates
title_auth The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates
title_full The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates
title_fullStr The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates
title_full_unstemmed The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates
title_short The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates
title_sort the application of association rules to detect the effects of vaccinations against covid-19 in the eu-27. preliminary estimates
topic Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
url https://sciendo.com/article/10.15611/eada.2023.1.01