Compare risk and utility across multiple scenarios

Measures risk and utility for multiple sets of CKM parameters from a table, using one randomly generated set of record keys.

Usage

assess_RUs(
  df,
  cat_vars,
  hrc_vars = NULL,
  parametres,
  confident,
  gv = 50,
  pv = 20,
  seed = NULL
)

Arguments

df

data.frame. Input microdata

cat_vars

Character vector. Categorical variables

hrc_vars

Named list. Hierarchical variables

parametres

data.frame. Parameter combinations to test with columns D, V, js

confident

integer. Official confidentiality threshold

gv

integer. Threshold defining large counts (default: 50)

pv

integer. Threshold defining small counts (default: 20)

seed

integer. Random seed number. If NULL, uses parent program's seed

Value

data.frame with nrow(parametres) rows containing risk and utility measures

Random seed

With this function, it is recommended to use the seed= argument if you want all scenarios to benefit from the same random seed and ensure results allow fair comparison between scenarios.

Examples

if (FALSE) { # \dontrun{
parametres <- build_parameters_table(c(10,15), c(10,20), js = 5)
res_RUs <- assess_RUs(
  df = dtest,
  cat_vars = c("REG", "DIPLOME", "SEXE", "AGE"),
  parametres = parametres,
  confident = 10,
  seed = 1234
)
} # }