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synMicrodata  

Synthetic Microdata Generator
View on CRAN: Click here


Download and install synMicrodata package within the R console
Install from CRAN:
install.packages("synMicrodata")

Install from Github:
library("remotes")
install_github("cran/synMicrodata")

Install by package version:
library("remotes")
install_version("synMicrodata", "2.1.0")



Attach the package and use:
library("synMicrodata")
Maintained by
Hang J. Kim
[Scholar Profile | Author Map]
First Published: 2023-02-06
Latest Update: 2023-02-06
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) <doi:10.1080/01621459.2016.1174132>.
How to cite:
Hang J. Kim (2023). synMicrodata: Synthetic Microdata Generator. R package version 2.1.0, https://cran.r-project.org/web/packages/synMicrodata. Accessed 18 Apr. 2025.
Previous versions and publish date:
1.0.0 (2023-02-06 12:00), 2.0.0 (2024-04-07 10:00)
Other packages that cited synMicrodata R package
View synMicrodata citation profile
Other R packages that synMicrodata depends, imports, suggests or enhances
Complete documentation for synMicrodata
Functions, R codes and Examples using the synMicrodata R package
Some associated functions: Rcpp_modelobject-class . createModel . modelobject . multipleSyn . readData . 
Some associated R codes: LoadModule.R . R_functions.R .  Full synMicrodata package functions and examples
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