Journal article Open Access
<?xml version='1.0' encoding='utf-8'?> <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.3990666</identifier> <creators> <creator> <creatorName>Roukema, Boudewijn F.</creatorName> <givenName>Boudewijn F.</givenName> <familyName>Roukema</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3772-0250</nameIdentifier> <affiliation>Nicolaus Copernicus University</affiliation> </creator> </creators> <titles> <title>Anti-clustering in the national SARS-CoV-2 daily infection counts</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2020</publicationYear> <subjects> <subject>COVID-19</subject> <subject>Data validation</subject> <subject>Poisson point process</subject> <subject>SARS-CoV-2</subject> </subjects> <dates> <date dateType="Issued">2020-07-23</date> </dates> <language>en</language> <resourceType resourceTypeGeneral="Text">Journal article</resourceType> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3990666</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="arXiv" relationType="IsSupplementTo" resourceTypeGeneral="Text">arXiv:2007.11779</relatedIdentifier> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3951151</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/covid-19</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/ncu</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/zenodo</relatedIdentifier> </relatedIdentifiers> <version>252cf1c</version> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><p>Produced and source files for &quot;Anti-clustering in the national SARS-CoV-2 daily infection counts&quot;, 2020, by B. F. Roukema</p> <ul> <li>subpoisson-02548e9.pdf - article in pdf format</li> <li>WP_C19CCTF_SARSCoV2.dat - Wikipedia COVID-19 Case Count Task Force (C19CCTF) medical cases chart data on national daily SARS-CoV-2 infections in csv format; URLs of the specific versions of the source pages are included</li> <li>WHO_vs_WP_jumps.dat - plain text table comparing jumpiness of WHO to C19CCTF national case count data</li> <li>phi_N_full.dat - results: clustering parameter phi_i for full national daily infection counts above a threshold of 50 per day</li> <li>phi_N_28days.dat - as for phi_N_full.dat, for the least noisy 28-day subsequence for each country</li> <li>phi_N_14days.dat - as for phi_N_28days.dat, for 14-day subsequences</li> <li>phi_N_07days.dat - as for phi_N_28days.dat, for 7-day subsequences</li> <li>four files phi_N*_jhu.dat which are equivalent to the main tables, but for the JHU CSSE data, as listed in the appendix of the article</li> <li>subpoisson-02548e9-git.bundle - git source package that can be unbundled with &#39;git clone subpoisson-02548e9-git.bundle&#39; and used for reproducibility: to download data, do calculations, analyse them, plot them and produce the article pdf</li> <li>subpoisson-02548e9-arXiv.tar.gz - source package for producing the article pdf, together with the reproducibility package, but without the git history; appropriate for ArXiv</li> <li>software-252cf1c.tar.gz - this should contain all the software, apart from a minimal POSIX-compatible system, needed for compiling and installing the software used in producing this paper</li> </ul> <p>Associated resources:</p> <ul> <li>ArXiv preprints: <a href="https://arXiv.org/abs/2007.11779">arXiv:2007.11779</a></li> <li>Software Heritage (swh): <a href="https://archive.softwareheritage.org/swh:1:dir:fcc9d6b111e319e51af88502fe6b233dc78d5166">swh:1:dir:fcc9d6b111e319e51af88502fe6b233dc78d5166</a></li> <li>Pop-science description: <a href="https://codeberg.org/boud/subpoisson/src/branch/subpoisson/README-popular-science.md">What is noisiness in SARS-CoV-2 daily infection counts?</a></li> </ul> <p>All the materials here are free-licensed, as stated in the individual files and packages.</p></description> </descriptions> </resource>
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