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