calculate_TAE: Calculate the total absolute error (TAE) between sample data...
In synthACS: Synthetic Microdata and Spatial MicroSimulation Modeling for ACS Data

Description Usage Arguments Examples

View source: R/sim_annealing.R

Calculates the total absolute error (TAE) between sample micro data and constraining totals from the matching macro data. Allows for updating of prior TAE instead of re-calculating to improve speed in iterating. The updating feature is particularly helpful for optimizing micro data fitting via simulated annealing (see optimize_microdata).

1 2	calculate_TAE(sample_data, constraint_list, prior_sample_totals = NULL, dropped_obs_totals = NULL, new_obs = NULL)

`sample_data`	A `data.frame` with attributes matching `constraint_list`.
`constraint_list`	A `list` of constraints. See `add_constraint`.
`prior_sample_totals`	An optional `list` containing attribute counts of a prior sample corresponding to the constraint list. Defaults to `NULL`.
`dropped_obs_totals`	An optional `list` containing attribute counts from the dropped observations in a prior sample. Defaults to `NULL`.
`new_obs`	An optional `data.frame` containing new observations with attributes matching those in `sample_data`, `constraint_list`, and `prior_sample_totals`. Defaults to `NULL`.

## Not run: 
## assumes that you have a micro_synthetic dataset named test_micro and attribute count
## named g respectively 
c_list <- add_constraint(attr_name= "gender", attr_totals= g, micro_data= test_micro,
            constraint_list= c_list)
calculate_TAE(test_micro, c_list)

## End(Not run)