January 20, 2022 Software Open Access

Badr, Hamada S.; Bürkner, Paul-Christian

DataCite XML Export

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<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="DOI">10.5281/zenodo.5884879</identifier>
  <creators>
    <creator>
      <creatorName>Badr, Hamada S.</creatorName>
      <givenName>Hamada S.</givenName>
      <familyName>Badr</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-9808-2344</nameIdentifier>
    </creator>
    <creator>
      <creatorName>Bürkner, Paul-Christian</creatorName>
      <givenName>Paul-Christian</givenName>
      <familyName>Bürkner</familyName>
    </creator>
  </creators>
  <titles>
    <title>bayesian: Bindings for Bayesian TidyModels</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2022</publicationYear>
  <subjects>
    <subject>bayesian</subject>
    <subject>brms</subject>
    <subject>stan</subject>
    <subject>tidymodels</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2022-01-20</date>
  </dates>
  <resourceType resourceTypeGeneral="Software"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5884879</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsSupplementTo">https://github.com/hsbadr/bayesian/tree/0.0.8</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4426836</relatedIdentifier>
  </relatedIdentifiers>
  <version>0.0.8</version>
  <rightsList>
    <rights rightsURI="https://opensource.org/licenses/MIT">MIT License</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Fit Bayesian models using 'brms'/'Stan' with 'parsnip'/'tidymodels' via 'bayesian' . 'tidymodels' is a collection of packages for machine learning; see Kuhn and Wickham (2020) ). The technical details of 'brms' and 'Stan' are described in Bürkner (2017) , Bürkner (2018) , and Carpenter et al. (2017) .</description>
    <description descriptionType="Other">To cite package "bayesian" in publications use:</description>
  </descriptions>
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