diffatQuantile

The vector output of a non-differentially private CDF
computation (cumulative count bins).

The vector output of a differentially private CDF 
computation (cumulative count bins).

A quantile value between 0 and 1, defaults to 0.5
for the median.

quantile

Optionally add additional parameters. This is primarily used to allow automated
execution of varied diagnostic functions.


Find the error (between 0 and 1) introduced by DP-Noise at a
   given quantile in the CDF


Designed by and for the community of differential privacy algorithm developers. It can be used to empirically evaluate and visualize Cumulative Distribution Functions incorporating noise that satisfies differential privacy, with numerous options made to streamline collection of utility measurements across variations of key parameters, such as epsilon, domain size, sample size, data shape, etc. Developed by researchers at Harvard PSI.

diffatQuantile: Determine the distance between CDFs at key quantiles.

Description

Usage

Arguments

Value

Examples