Build table and apply Cell Key Method

This function constructs a contingency table from microdata and applies the Cell Key Method for statistical disclosure control.

Usage

tabulate_and_apply_ckm(
  df,
  rk_var = "rkey",
  cat_vars = NULL,
  hrc_vars = NULL,
  num_var = NULL,
  marge_label = "Total",
  D,
  V,
  js = 0,
  I = NULL,
  J = NULL,
  stack = NULL,
  ...
)

Arguments

df

data.frame. Input microdata

rk_var

Character. Individual key variable (NULL for no keys)

cat_vars

Character vector. Categorical variables

hrc_vars

Named list. Hierarchical variables

num_var

Character. Numerical variable to aggregate

marge_label

Character. Margin label (default: "Total")

D

integer. Deviation parameter (must be strictly positive)

V

numeric. Noise variance (must be strictly positive)

js

integer. Threshold for sensitive values (default: 0). If js=0, only value 0 will be forbidden

I

integer vector. Original values to consider

J

integer vector. Perturbed values to consider

stack

Named list of parameters (D, V) to produce a stacked matrix with these parameters applied only on the large counts. js is set to 0 for this part.

...

Additional parameters passed to transition matrix creation

Value

A list containing the perturbed table and transition matrix

Examples

if (FALSE) { # \dontrun{
data("dtest")
set.seed(123)
dtest_avec_cles <- build_individual_keys(dtest)

res_ckm <- tabulate_and_apply_ckm(
  df = dtest_avec_cles,
  cat_vars = c("DIPLOME", "SEXE", "AGE"),
  hrc_vars = list(GEO = c("REG", "DEP")),
  marge_label = "Total",
  D = 10, V = 15, js = 4
)

# With a stacked matrix
res_ckm1 <- tabulate_and_apply_ckm(
  df = dtest_avec_cles,
  cat_vars = c("DIPLOME", "SEXE", "AGE"),
  hrc_vars = list(GEO = c("REG", "DEP")),
  marge_label = "Total",
  D = 10, V = 15, js = 4,
  stack = list(D = 10, V = 5)
)
} # }