covDataAccess: Differentially Private Covariance Data Access Function

In DPpack: Differentially Private Statistical Analysis and Machine Learning

Differentially Private Covariance Data Access Function

Description

This function performs the data access step in the computation of a differentially private covariance. The true values are computed using cov, while the sensitivities are calculated based on bounded and unbounded differential privacy \insertCiteKifer2011DPpack according to the theoretical values \insertCiteLiu2019bDPpack. For the covariance, the sensitivities based on bounded and unbounded differential privacy are identical, so only one value is returned.

Usage

covDataAccess(x1, x2, lower.bound1, upper.bound1, lower.bound2, upper.bound2)

Arguments

x1, x2	Numeric vectors whose covariance is desired.
lower.bound1, lower.bound2	Real numbers giving the lower bounds of x1 and x2, respectively.
upper.bound1, upper.bound2	Real numbers giving the upper bounds of x1 and x2, respectively.

Value

List of the true covariance and the sensitivity calculated based on theoretical values.

References

\insertRef

Liu2019bDPpack

\insertRef

Kifer2011DPpack

Examples

covDataAccess(c(1,4,3,2), c(-2,-3,-4,-1), 0, 5, -5, 0)

DPpack documentation built on April 8, 2023, 9:09 a.m.