Description Usage Arguments Value References Examples
A general case of iterative proportional fitting. It can satisfy two, disparate sets of marginals that do not agree on a single total. A common example is balancing population data using household- and person-level marginal controls. This could be for survey expansion or synthetic population creation. The second set of marginal/seed data is optional, meaning it can also be used for more basic IPF tasks.
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primary_seed |
In population synthesis or household survey expansion, this would be the household seed table (each record would represent a household). It could also be a trip table, where each row represents an origin-destination pair. |
primary_targets |
A |
secondary_seed |
Most commonly, if the primary_seed describes
households, the secondary seed table would describe the persons in each
household. Must contain the same |
secondary_targets |
Same format as |
primary_id |
The field used to join the primary and secondary seed
tables. Only necessary if |
secondary_importance |
A |
relative_gap |
After each iteration, the weights are compared to the
previous weights and the
the |
max_iterations |
maximum number of iterations to perform, even if
|
absolute_diff |
Upon completion, the For example, if if a target value was 2, and the expanded weights equaled 1, that's a 100 is only 1. Defaults to 10. |
weight_floor |
Minimum weight to allow in any cell to prevent zero weights. Set to .0001 by default. Should be arbitrarily small compared to your seed table weights. |
verbose |
Print iteration details and worst marginal stats upon
completion? Default |
max_ratio |
|
min_ratio |
|
a named list
with the primary_seed
with weight, a
histogram of the weight distribution, and two comparison tables to aid in
reporting.
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.537.723&rep=rep1&type=pdf
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