Generates a random sample from the observed data.
syn.sample(y, xp, smoothing, cont.na, proper = FALSE, ...)an original data vector of length n.
a target length k of a synthetic data vector.
smoothing method for a continous variable.
a vector of codes for missing values for continuous variables that should be excluded from smoothing.
if proper = TRUE values are sampled from
a bootstrapped sample of the original data.
additional parameters passed to sample.
A vector of length k with synthetic values.
A simple random sample with replacement is taken from the
observed values in y and used as synthetic values.
A Guassian kernel smoothing can be applied to continuous variables
by setting smoothing parameter to "density". It is recommended
as a tool to decrease the disclosure risk.