Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Creating pull request for 10.21105.joss.03705 #2714

Merged
merged 2 commits into from
Oct 27, 2021
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
177 changes: 177 additions & 0 deletions joss.03705/10.21105.joss.03705.crossref.xml
Original file line number Diff line number Diff line change
@@ -0,0 +1,177 @@
<?xml version="1.0" encoding="UTF-8"?>
<doi_batch xmlns="http://www.crossref.org/schema/4.4.0" xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" xmlns:rel="http://www.crossref.org/relations.xsd" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" version="4.4.0" xsi:schemaLocation="http://www.crossref.org/schema/4.4.0 http://www.crossref.org/schemas/crossref4.4.0.xsd">
<head>
<doi_batch_id>9171a787a2d7fdaabcfa86b570720696</doi_batch_id>
<timestamp>20211027154314</timestamp>
<depositor>
<depositor_name>JOSS Admin</depositor_name>
<email_address>[email protected]</email_address>
</depositor>
<registrant>The Open Journal</registrant>
</head>
<body>
<journal>
<journal_metadata>
<full_title>Journal of Open Source Software</full_title>
<abbrev_title>JOSS</abbrev_title>
<issn media_type="electronic">2475-9066</issn>
<doi_data>
<doi>10.21105/joss</doi>
<resource>https://joss.theoj.org</resource>
</doi_data>
</journal_metadata>
<journal_issue>
<publication_date media_type="online">
<month>10</month>
<year>2021</year>
</publication_date>
<journal_volume>
<volume>6</volume>
</journal_volume>
<issue>66</issue>
</journal_issue>
<journal_article publication_type="full_text">
<titles>
<title>serp: An R package for smoothing in ordinal regression</title>
</titles>
<contributors>
<person_name sequence="first" contributor_role="author">
<given_name>Ejike</given_name>
<surname>Ugba</surname>
<ORCID>http://orcid.org/0000-0003-2572-0023</ORCID>
</person_name>
</contributors>
<publication_date>
<month>10</month>
<day>27</day>
<year>2021</year>
</publication_date>
<pages>
<first_page>3705</first_page>
</pages>
<publisher_item>
<identifier id_type="doi">10.21105/joss.03705</identifier>
</publisher_item>
<ai:program name="AccessIndicators">
<ai:license_ref applies_to="vor">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
<ai:license_ref applies_to="am">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
<ai:license_ref applies_to="tdm">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
</ai:program>
<rel:program>
<rel:related_item>
<rel:description>Software archive</rel:description>
<rel:inter_work_relation relationship-type="references" identifier-type="doi">“https://doi.org/10.5281/zenodo.5596864”</rel:inter_work_relation>
</rel:related_item>
<rel:related_item>
<rel:description>GitHub review issue</rel:description>
<rel:inter_work_relation relationship-type="hasReview" identifier-type="uri">https://github.com/openjournals/joss-reviews/issues/3705</rel:inter_work_relation>
</rel:related_item>
</rel:program>
<doi_data>
<doi>10.21105/joss.03705</doi>
<resource>https://joss.theoj.org/papers/10.21105/joss.03705</resource>
<collection property="text-mining">
<item>
<resource mime_type="application/pdf">https://joss.theoj.org/papers/10.21105/joss.03705.pdf</resource>
</item>
</collection>
</doi_data>
<citation_list>
<citation key="ref1">
<doi>10.1002/9780470594001</doi>
</citation>
<citation key="ref2">
<doi>10.1111/j.2517-6161.1980.tb01109.x</doi>
</citation>
<citation key="ref3">
<unstructured_citation>Fisher, F, The identification problem in econometrics, McGraw-Hill, 1966</unstructured_citation>
</citation>
<citation key="ref4">
<doi>10.2307/2682804</doi>
</citation>
<citation key="ref5">
<doi>10.1007/978-0-387-84858-7</doi>
</citation>
<citation key="ref6">
<doi>10.1007/978-3-642-20192-9</doi>
</citation>
<citation key="ref7">
<unstructured_citation>serp: Smooth Effects on Response Penalty for CLM, Ugba, E R, R package version 0.2.0, 2021, https://CRAN.R-project.org/package=serp</unstructured_citation>
</citation>
<citation key="ref8">
<unstructured_citation>R: A language and environment for statistical computing, R Core Team, R Foundation for Statistical Computing, Vienna, Austria, 2021, https://www.R-project.org/</unstructured_citation>
</citation>
<citation key="ref9">
<doi>10.3390/stats4030037</doi>
</citation>
<citation key="ref10">
<doi>10.1177/1471082X16642560</doi>
</citation>
<citation key="ref11">
<doi>10.1111/j.2517-6161.1996.tb02095.x</doi>
</citation>
<citation key="ref12">
<doi>10.18637/jss.v032.i10</doi>
</citation>
<citation key="ref13">
<unstructured_citation>ordinal—Regression Models for Ordinal Data, Christensen, R H B, 2019, R package version 2019.12-10, https://CRAN.R-project.org/package=ordinal</unstructured_citation>
</citation>
<citation key="ref14">
<unstructured_citation>Modern Applied Statistics with S, Venables, W N and Ripley, B D, Springer, Fourth, New York, 2002, ISBN 0-387-95457-0, https://www.stats.ox.ac.uk/pub/MASS4/</unstructured_citation>
</citation>
<citation key="ref15">
<unstructured_citation>SAS/STAT User’s Guide Procedures, SAS Institute Inc, SAS Institute Inc., Cary, NC, 2018, http://support.sas.com/documentation/onlinedoc/stat/indexproc.html</unstructured_citation>
</citation>
<citation key="ref16">
<unstructured_citation>IBM Corp., IBM SPSS Statistics for Windows, https://www.ibm.com/analytics/spss-statistics-software, 28.0, Armonk, NY: IBM Corp, 2021</unstructured_citation>
</citation>
<citation key="ref17">
<doi>10.1111/j.2517-6161.1996.tb02080.x</doi>
</citation>
<citation key="ref18">
<doi>10.1080/00401706.2000.10485983</doi>
</citation>
<citation key="ref19">
<doi>10.1111/j.1467-9868.2005.00503.x</doi>
</citation>
<citation key="ref20">
<unstructured_citation>glmnetcr: Fit a penalized constrained continuation ratio model for predicting an ordinal response, Archer, K J, https://cran.r-project.org/package=glmnetcr, R package version 1.0.6, 2014</unstructured_citation>
</citation>
<citation key="ref21">
<unstructured_citation>glmpathcr: Fit a penalized continuation ratio model for predicting an ordinal response, Archer, K J, https://cran.r-project.org/package=glmpathcr, R package version 1.0.8, 2014</unstructured_citation>
</citation>
<citation key="ref22">
<unstructured_citation>rms: Regression Modeling Strategies, Harrell Jr, F E, R package version 6.2-0, 2021, https://CRAN.R-project.org/package=rms</unstructured_citation>
</citation>
<citation key="ref23">
<doi>10.4137/CIN.S20806</doi>
</citation>
<citation key="ref24">
<doi>10.18637/jss.v099.i06</doi>
</citation>
<citation key="ref25">
<unstructured_citation>Understanding the bias-variance tradeoff, Fortmann-Roe, S, 2012, http://scott.fortmann-roe.com/docs/BiasVariance.html</unstructured_citation>
</citation>
<citation key="ref26">
<doi>10.1080/01621459.2016.1180986</doi>
</citation>
<citation key="ref27">
<doi>10.1002/bimj.4710310703</doi>
</citation>
<citation key="ref28">
<unstructured_citation>Christensen, R H B, Cumulative Link Models for Ordinal Regression with the R Package ordinal, https://cran.r-project.org/web/packages/ordinal/vignettes/clm_article.pdf, Accessed: 2021-08-25, 2019</unstructured_citation>
</citation>
<citation key="ref29">
<doi>10.1002/wics.1296</doi>
</citation>
<citation key="ref30">
<doi>10.2307/2347760</doi>
</citation>
<citation key="ref31">
<unstructured_citation>pkgdown: Make static HTML documentation for a package, Wickham, H and Hesselberth, J, R package version 1.6.1, 2020, https://CRAN.R-project.org/package=pkgdown</unstructured_citation>
</citation>
</citation_list>
</journal_article>
</journal>
</body>
</doi_batch>
Binary file added joss.03705/10.21105.joss.03705.pdf
Binary file not shown.