syn.rf

an original data vector of length <code>n</code>.

a matrix (<code>n</code> x <code>p</code>) of original covariates.

a matrix (<code>k</code> x <code>p</code>) of synthesised covariates.

smoothing method for continuous variables.

smoothing

proper

ntree

additional parameters passed to 
 <code><a rd-options="randomForest" href="/link/randomForest?package=synthpop&version=1.5-1&to=randomForest" data-mini-rdoc="randomForest::randomForest">randomForest</a></code>.

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Generates univariate synthetic data using Breiman's random forest algorithm 
classification and regression. It uses <code><a rd-options="" href="/link/randomForest?package=synthpop&version=1.5-1" data-mini-rdoc="synthpop::randomForest">randomForest</a></code> function 
from the randomForest package.

datagen

A tool for producing synthetic versions of microdata containing confidential information so that they are safe to be released to users for exploratory analysis. The key objective of generating synthetic data is to replace sensitive original values with synthetic ones causing minimal distortion of the statistical information contained in the data set. Variables, which can be categorical or continuous, are synthesised one-by-one using sequential modelling. Replacements are generated by drawing from conditional distributions fitted to the original data using parametric or classification and regression trees models. Data are synthesised via the function syn() which can be largely automated, if default settings are used, or with methods defined by the user. Optional parameters can be used to influence the disclosure risk and the analytical quality of the synthesised data. For a description of the implemented method see Nowok, Raab and Dibben (2016) <doi:10.18637/jss.v074.i11>.

Beata Nowok

synthpop

Generating Synthetic Versions of Sensitive Microdata for
Statistical Disclosure Control

syn.rf function

additional parameters passed to 
 <code><a rd-options='randomForest' href='randomForest'>randomForest</a></code>.

Generates univariate synthetic data using Breiman's random forest algorithm 
classification and regression. It uses <code><a rd-options='' href='randomForest'>randomForest</a></code> function 
from the randomForest package.

syn.rf: Synthesis with random forest

Description

Usage

Arguments

Value

Details

References

See Also