Desired AbcSmc Operational Modes

[pearsonca]

• [x] traditional fitting: start with functional priors, do a sequence of waves, get a resulting posterior
• [x] traditional scenario analysis / projection: start with posterior + scenario grid, run projections for scenarios for each particle in posterior, collect outcomes
• [ ] model selection fitting: start with model grid + priors for parameters (possibly model specific), estimate those parameters, compare model selection criteria => indicate preferred model
• [ ] iterative fitting: start with some priors, some fixed values => do waves => change which priors fixed vs sampled => do waves => ... => get "full" posterior (potentially also change metrics as waves go along)
• [ ] model scenario fitting => projection: start with model grid + priors => fitting => carry forward grid plus distinct posteriors into scenario analysis

[pearsonca]

• [ ] fitting model against multiple datasets, with some elements shared and some by-context (location-/population-specific etc)