anovir
Analysis of Virulence
Epidemiological population dynamics models traditionally define a pathogen's virulence as the increase in the per capita rate of mortality of infected hosts due to infection. This package provides functions allowing virulence to be estimated by maximum likelihood techniques. The approach is based on the analysis of relative survival comparing survival in matching cohorts of infected vs. uninfected hosts (Agnew 2019) doi:10.1101/530709.
- Version0.1.0
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release10/24/2020
Documentation
- VignetteIntroduction
- VignetteConfidence intervals
- VignetteData format
- VignetteLikelihood functions described
- VignetteModifying nll functions
- VignetteUsing nll functions
- VignetteProbability distribution functions
- VignetteStarting values
- VignetteThe exponential distribution
- VignetteWorked examples I
- VignetteWorked examples II
Team
Philip Agnew
Jimmy Lopez
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 215 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 12 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 2,571 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 Jul 23, 2024 with 34 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
- Depends1 package
- Suggests3 packages