IdentificationRisk: An Identification Risk Function

In RyanHornby/IdentificationRisk: Calculates Identification Risk for Synthetic Data

Description

This function will compute the identification risk for a dataset with synthetic categorical variables. This function assumes categorical variables will be as factors.

Usage

IdentificationRisk(
  origdata,
  syndata,
  known,
  syn,
  r,
  percentage = TRUE,
  euclideanDist = FALSE
)

Arguments

origdata	dataframe of the original data
syndata	list of the different synthetic dataframes
known	vector of the names of the columns in the dataset assumed to be known
syn	vector of the names of the columns in the dataset that are synthetic
r	radius to compare with for continuous variables. Radius is either percentage (default) or fixed. Radius can be the same for all continuous variables or specific to each. To specify for each use a vector, with the radii ordered in the same order those columns appear in the dataset.
percentage	true for a percentage radius, false for a constant radius
euclideanDist	true for a euclidean distance radius, false otherwise

RyanHornby/IdentificationRisk documentation built on May 8, 2021, 5:23 a.m.