Build a synthetic population of individuals where we only have aggregate statistics
Typical problems solved:
Area statistics need reaggregating to different spatial units
Need to estimate missing population statistics
Need an individual level population for modelling
Spatial vs aspatial
Static vs dynamic:
Dynamic uses transitional probabilities to roll static forward in time as a model.
Integer vs probabilistic
We're going to look at spatial static integer based microsimulation
We have area statistics and wasn't to recreate the underlying population
e.g. census statistics
We need a sample of a population with the same characteristics/P>
e.g. census sample of anonymised records, British household panel survey
We fill the areas with individuals randomly
We then subtract an individual and add in a new one
If the aggregate statistics improve, we keep the change, otherwise we revert
We repeat until our error is ok
Are other methods resulting in probabilistic/floating-point populations, for example, iterative proportional fitting
At this point we have a disaggregated population
However, if our microdata individuals have other variables attached to them that are correlated with the constraining variables, we now have an estimate of these in our area populations
Standard regression will give us a lower bound on the quality of this estimate
Reaggregate to new geography
Roll individuals forward in time using probabilities of life changes, based on scenarios
Use as basis for agent based models etc.
Flexible Modelling Framework by Kirk Harland
Modular, also comes with cluster analysis and graphing plugins. Just delete jar files and reboot if you don't want them
Open source, so security can be checked