StdDiffpdf

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 vector length 2 containing user-specified min and max 
Note that the gran and range must be the same as used to make the DP-CDF!

range

The smallest unit of measurement in the data (one [year]
for a list of ages)

gran

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


Calculate difference between the private Standard Deviation and the original Standard Deviation (from CDFs)


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.

StdDiffpdf: Error in Standard Deviation from CDF

Description

Usage

Arguments

Value