BSTZINB
Association Among Disease Counts and Socio-Environmental Factors
Estimation of association between disease or death counts (e.g. COVID-19) and socio-environmental risk factors using a zero-inflated Bayesian spatiotemporal model. Non-spatiotemporal models and/or models without zero-inflation are also included for comparison. Functions to produce corresponding maps are also included. See Chakraborty et al. (2022) doi:10.1007/s13253-022-00487-1 for more details on the method.
- Version2.0.0
- R versionR (≥ 2.10)
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release01/30/2025
Documentation
Team
Suman Majumder
MaintainerShow author detailsTanujit Dey
Show author detailsRolesContributorSounak Chakraborty
Show author detailsRolesContributorChae-Young Lim
Show author detailsRolesContributorYoon-Bae Jun
Show author detailsRolesAuthor, Copyright holder
Insights
Last 30 days
This package has been downloaded 215 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,254 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jan 30, 2025 with 48 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports14 packages
- Suggests5 packages