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synMicrodata (version 2.1.3)

Synthetic Microdata Generator

Description

This tool fits a non-parametric Bayesian model called a "hierarchically coupled mixture model with local dependence (HCMM-LD)" to the original microdata in order to generate synthetic microdata for privacy protection. The non-parametric feature of the adopted model is useful for capturing the joint distribution of the original input data in a highly flexible manner, leading to the generation of synthetic data whose distributional features are similar to that of the input data. The package allows the original input data to have missing values and impute them with the posterior predictive distribution, so no missing values exist in the synthetic data output. The method builds on the work of Murray and Reiter (2016) .

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Version

Install

install.packages('synMicrodata')

Monthly Downloads

250

Version

2.1.3

License

GPL (>= 3)

Maintainer

Juhee Lee

Last Published

November 26th, 2025

Functions in synMicrodata (2.1.3)

plot.synMicro_object

Plot Comparing Synthetic Data with Original Input Data
modelobject

RCPP Implementation of the Library
summary.synMicro_object

Summarizing synthesis results
createModel

Create a model object
multipleSyn

Generate synthetic micro datasets
readData

Read the original datasets
Rcpp_modelobject-class

Class "Rcpp_modelobject"