This function sets up the skeleton of an analysis to go from seroprevalence data to the ROI estimation surface.
That skeleton uses a series of separate scripts for each analytical step (fitting, simulation, analysis, and application),
connected via the command line build tool make
. This approach allows clean substitution for various stages (e.g.,
using a different model to generate life histories). The following files are created:
- Makefile
the dependencies for various analysis stages
- README.md
brief notes about project parts
- fit.R
script for fitting seroprevalence data
- synthesize.R
script for generating synthetic populations
- digest.R
script for converting life histories into probability coefficients for ROI calculation
- simple.R
a quick example start-to-finish analysis