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synthpop

Generating Synthetic Versions of Sensitive Microdata for Statistical Disclosure Control

Installation

About

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.

Citation synthpop citation info
www.synthpop.org.uk/

Key Metrics

Version 1.8-0
Published 2022-08-31 604 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks synthpop results

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Maintainer

Maintainer

Beata Nowok

beata.nowok@gmail.com

Authors

Beata Nowok

aut / cre

Gillian M Raab

aut

Chris Dibben

ctb

Joshua Snoke

ctb

Caspar van Lissa

ctb

Material

NEWS
Reference manual
Package source

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Inference in synthpop
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Utility

macOS

r-release

arm64

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arm64

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x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

synthpop archive

Imports

lattice
MASS
methods
nnet
ggplot2
graphics
stats
utils
rpart
party
foreign
plyr
proto
polspline
randomForest
ranger
classInt
mipfp
survival
stringr
rmutil
broman

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