new_privacy: 'privacy' Object Constructor.
In dapper: Data Augmentation for Private Posterior Estimation

new_privacy

R Documentation

`privacy` Object Constructor.

Creates a privacy object to be used as input into dapper_sample().

new_privacy(
  post_f = NULL,
  latent_f = NULL,
  priv_f = NULL,
  st_f = NULL,
  npar = NULL,
  varnames = NULL
)

`post_f`	a function that draws posterior samples given the confidential data.
`latent_f`	a function that represents the latent data sampling model.
`priv_f`	a function that represents the log likelihood of the privacy mechanism.
`st_f`	a function that calculates the statistic to be released.
`npar`	dimension of the parameter being estimated.
`varnames`	an optional character vector of parameter names. Used to label summary outputs.

post_f() is a function which makes draws from the posterior sampler. It has the syntax post_f(dmat, theta). Here dmat is a numeric matrix representing the confidential database and theta is a numeric vector which serves as the initialization point for a one sample draw. The easiest, bug-free way to construct post_f() is to use a conjugate prior. However, this function can also be constructed by wrapping a MCMC sampler generated from other R packages (e.g. rstan, fmcmc, adaptMCMC).
priv_f() is a function that represents the log of the privacy mechanism density. This function has the form priv_f(sdp, sx) where sdp and sx are both either a numeric vector or matrix. The arguments must appear in the exact stated order with the same variables names as mentioned. Finally, the return value of priv_f() must be a numeric vector of length one.
st_f() is a function which calculates a summary statistic. It has the syntax st_f(xi, sdp, i) where the three arguments must appear in the stated order. The role of this function is to represent terms in the definition of record additivity. Here i is an integer, while xi is an numeric vector and sdp is a numeric vector or matrix.
npar is an integer equal to the dimension of theta.