-
Notifications
You must be signed in to change notification settings - Fork 21
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #4615 from openjournals/joss.05612
Merging automatically
- Loading branch information
Showing
3 changed files
with
748 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,230 @@ | ||
<?xml version="1.0" encoding="UTF-8"?> | ||
<doi_batch xmlns="http://www.crossref.org/schema/5.3.1" | ||
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="5.3.1" | ||
xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schemas/crossref5.3.1.xsd"> | ||
<head> | ||
<doi_batch_id>20230926T103117-00ea19afc9996f096835500cbd3a6d23a1d37b3a</doi_batch_id> | ||
<timestamp>20230926103117</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>09</month> | ||
<year>2023</year> | ||
</publication_date> | ||
<journal_volume> | ||
<volume>8</volume> | ||
</journal_volume> | ||
<issue>89</issue> | ||
</journal_issue> | ||
<journal_article publication_type="full_text"> | ||
<titles> | ||
<title>Bernadette: Bayesian Inference and Model Selection for | ||
Stochastic Epidemics in R</title> | ||
</titles> | ||
<contributors> | ||
<person_name sequence="first" contributor_role="author"> | ||
<given_name>Lampros</given_name> | ||
<surname>Bouranis</surname> | ||
<ORCID>https://orcid.org/0000-0002-1291-2192</ORCID> | ||
</person_name> | ||
</contributors> | ||
<publication_date> | ||
<month>09</month> | ||
<day>26</day> | ||
<year>2023</year> | ||
</publication_date> | ||
<pages> | ||
<first_page>5612</first_page> | ||
</pages> | ||
<publisher_item> | ||
<identifier id_type="doi">10.21105/joss.05612</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">10.5281/zenodo.8376673</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/5612</rel:inter_work_relation> | ||
</rel:related_item> | ||
</rel:program> | ||
<doi_data> | ||
<doi>10.21105/joss.05612</doi> | ||
<resource>https://joss.theoj.org/papers/10.21105/joss.05612</resource> | ||
<collection property="text-mining"> | ||
<item> | ||
<resource mime_type="application/pdf">https://joss.theoj.org/papers/10.21105/joss.05612.pdf</resource> | ||
</item> | ||
</collection> | ||
</doi_data> | ||
<citation_list> | ||
<citation key="bouranis"> | ||
<article_title>Bayesian analysis of diffusion-driven | ||
multi-type epidemic models with application to COVID-19</article_title> | ||
<author>Bouranis</author> | ||
<doi>10.48550/arXiv.2211.15229</doi> | ||
<cYear>2022</cYear> | ||
<unstructured_citation>Bouranis, L., Demiris, N., | ||
Kalogeropoulos, K., & Ntzoufras, I. (2022). Bayesian analysis of | ||
diffusion-driven multi-type epidemic models with application to | ||
COVID-19. arXiv. | ||
https://doi.org/10.48550/arXiv.2211.15229</unstructured_citation> | ||
</citation> | ||
<citation key="bernadette"> | ||
<volume_title>Bernadette: Bayesian inference and model | ||
selection for stochastic epidemics</volume_title> | ||
<author>Bouranis</author> | ||
<cYear>2023</cYear> | ||
<unstructured_citation>Bouranis, L. (2023). Bernadette: | ||
Bayesian inference and model selection for stochastic epidemics. | ||
https://CRAN.R-project.org/package=Bernadette</unstructured_citation> | ||
</citation> | ||
<citation key="epidemia"> | ||
<article_title>epidemia: Modeling of epidemics using | ||
hierarchical Bayesian models</article_title> | ||
<author>Scott</author> | ||
<cYear>2020</cYear> | ||
<unstructured_citation>Scott, J., Gandy, A., Mishra, S., | ||
Unwin, J., Flaxman, S., & Bhatt, S. (2020). epidemia: Modeling of | ||
epidemics using hierarchical Bayesian models. | ||
https://imperialcollegelondon.github.io/epidemia/</unstructured_citation> | ||
</citation> | ||
<citation key="rsoft"> | ||
<volume_title>R: A language and environment for statistical | ||
computing</volume_title> | ||
<author>R Core Team</author> | ||
<cYear>2023</cYear> | ||
<unstructured_citation>R Core Team. (2023). R: A language | ||
and environment for statistical computing. R Foundation for Statistical | ||
Computing. https://www.R-project.org/</unstructured_citation> | ||
</citation> | ||
<citation key="rstan"> | ||
<article_title>RStan: The R interface to | ||
Stan</article_title> | ||
<author>Stan Development Team</author> | ||
<cYear>2023</cYear> | ||
<unstructured_citation>Stan Development Team. (2023). RStan: | ||
The R interface to Stan. https://mc-stan.org/</unstructured_citation> | ||
</citation> | ||
<citation key="carpenter2017stan"> | ||
<article_title>Stan: A probabilistic programming | ||
language</article_title> | ||
<author>Carpenter</author> | ||
<journal_title>Journal of statistical | ||
software</journal_title> | ||
<issue>1</issue> | ||
<volume>76</volume> | ||
<doi>10.18637/jss.v076.i01</doi> | ||
<cYear>2017</cYear> | ||
<unstructured_citation>Carpenter, B., Gelman, A., Hoffman, | ||
M., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, | ||
P., & Riddell, A. (2017). Stan: A probabilistic programming | ||
language. Journal of Statistical Software, 76(1), 1–32. | ||
https://doi.org/10.18637/jss.v076.i01</unstructured_citation> | ||
</citation> | ||
<citation key="epiestim"> | ||
<volume_title>EpiEstim: Estimate time varying reproduction | ||
numbers from epidemic curves</volume_title> | ||
<author>Cori</author> | ||
<cYear>2021</cYear> | ||
<unstructured_citation>Cori, A. (2021). EpiEstim: Estimate | ||
time varying reproduction numbers from epidemic curves. | ||
https://CRAN.R-project.org/package=EpiEstim</unstructured_citation> | ||
</citation> | ||
<citation key="Cori2013"> | ||
<article_title>A new framework and software to estimate | ||
time-varying reproduction numbers during epidemics</article_title> | ||
<author>Cori</author> | ||
<journal_title>American Journal of | ||
Epidemiology</journal_title> | ||
<issue>9</issue> | ||
<volume>178</volume> | ||
<doi>10.1093/aje/kwt133</doi> | ||
<cYear>2013</cYear> | ||
<unstructured_citation>Cori, A., Ferguson, N., Fraser, C., | ||
& Cauchemez, S. (2013). A new framework and software to estimate | ||
time-varying reproduction numbers during epidemics. American Journal of | ||
Epidemiology, 178(9), 1505–1512. | ||
https://doi.org/10.1093/aje/kwt133</unstructured_citation> | ||
</citation> | ||
<citation key="gostic"> | ||
<article_title>Practical considerations for measuring the | ||
effective reproductive number, Rt</article_title> | ||
<author>Gostic</author> | ||
<journal_title>PLoS Computational Biology</journal_title> | ||
<issue>12</issue> | ||
<volume>16</volume> | ||
<doi>10.1371/journal.pcbi.1008409</doi> | ||
<cYear>2020</cYear> | ||
<unstructured_citation>Gostic, K., McGough, L., Baskerville, | ||
E., Abbott, S., Joshi, K., Tedijanto, C., Kahn, R., Niehus, R., Hay, J., | ||
De Salazar, P., Hellewell, J., Meakin, S., Munday, J., Bosse, N., | ||
Sherrat, K. e., Thompson, R., White, L., Huisman, J., Scire, J., … | ||
Cobey, S. (2020). Practical considerations for measuring the effective | ||
reproductive number, Rt. PLoS Computational Biology, 16(12), 1–21. | ||
https://doi.org/10.1371/journal.pcbi.1008409</unstructured_citation> | ||
</citation> | ||
<citation key="brooks"> | ||
<volume_title>Handbook of Markov chain Monte | ||
Carlo</volume_title> | ||
<author>Brooks</author> | ||
<cYear>2011</cYear> | ||
<unstructured_citation>Brooks, S., Gelman, A., Jones, G., | ||
& Meng, X. (2011). Handbook of Markov chain Monte Carlo. CRC | ||
press.</unstructured_citation> | ||
</citation> | ||
<citation key="psisloo2"> | ||
<article_title>loo: Efficient leave-one-out cross-validation | ||
and WAIC for Bayesian models</article_title> | ||
<author>Vehtari</author> | ||
<cYear>2023</cYear> | ||
<unstructured_citation>Vehtari, A., Gabry, J., Magnusson, | ||
M., Yao, Y., Bürkner, P., Paananen, T., & Gelman, A. (2023). loo: | ||
Efficient leave-one-out cross-validation and WAIC for Bayesian models. | ||
https://mc-stan.org/loo/</unstructured_citation> | ||
</citation> | ||
<citation key="ward_react2"> | ||
<article_title>SARS-CoV-2 antibody prevalence in England | ||
following the first peak of the pandemic</article_title> | ||
<author>Ward</author> | ||
<journal_title>Nature Communications</journal_title> | ||
<volume>12</volume> | ||
<doi>10.1038/s41467-021-21237-w</doi> | ||
<cYear>2021</cYear> | ||
<unstructured_citation>Ward, H., Atchison, C., Whitaker, M., | ||
Ainslie, K., Elliott, J., Okell, L., Redd, R., Ashby, D., Donnelly, C., | ||
Barclay, W., Darzi, A., Cooke, G., Riley, S., & Elliott, P. (2021). | ||
SARS-CoV-2 antibody prevalence in England following the first peak of | ||
the pandemic. Nature Communications, 12, 905. | ||
https://doi.org/10.1038/s41467-021-21237-w</unstructured_citation> | ||
</citation> | ||
</citation_list> | ||
</journal_article> | ||
</journal> | ||
</body> | ||
</doi_batch> |
Oops, something went wrong.