DP4.Sim: Releasing 4 Differential Private RKHS smoothing means of a...

In sxz155/test:

Description

This function create 4 DP RKHS smoothing means from an existing data set with known eigenvalues and eigenvectors

Usage

DP4.Sim(alpha = rep(1, 4), beta = rep(0.1, 4), kernel = c("Exp", "M3/2",
  "M5/2", "Gau"), n = rep(100, 4), N = rep(25, 4), phi = rep(0.01, 4),
  ro = rep(0.2, 4), tau = rep(0.4, 4), case = rep(2, 4), pow = rep(4,
  4), mu = matrix(rep(0, 4 * 100), ncol = 4))

Arguments

alpha, beta	Privacy parameters, real numbers
n	real vector 4*1, number of grid points
N	real vector 4*1, number of observations
phi	real number, penalty parameter
ro	range parameter in kernel, real number
tau	range of the uniform distribution in KL expansion
pow	smoothing parameter, e.val.x_i=i^-pow
mu	real vector n*1, initial mean vector
e.val.x	real vector n*1, eigenvalues
e.vec.x	real valued matrix n*N, eigenvectors
e.val.z	real valued matrix n*N, eigenvectors of noise

Value

four DP_Sim output each of them includin "f.tilda","delta","f" and "X"

sxz155/test documentation built on May 30, 2019, 10:40 p.m.