Synthetic Microdata and Spatial MicroSimulation Modeling for ACS Data

Provides access to curated American Community Survey (ACS) base tables via a wrapper to library(acs). Builds synthetic micro-datasets at any user-specified geographic level with ten default attributes; and, conducts spatial microsimulation modeling (SMSM) via simulated annealing. SMSM is conducted in parallel by default. Lastly, we provide functionality for data-extensibility of micro-datasets.


synthACS provides four main features. Firstly, it provides a wrapper to library(acs) to access numerous American Community Survey (ACS) base tables which may be of interest to many researchers. Secondly, it builds synthetic microdatasets of ACS data (pulled via API) at any specified geographic level with 10 default individual attributes. Thirdly, synthACS provides funtionality for users to add additional ACS & non-ACS synthetic data-attributes to micro-datasets based on macro population characteristics. And finally, in addition to creating synthetic data, synthACS also conducts spatial microsimulation modeling (SMSM) (ie- optimally fits synthetic microdata to macrodata constraints) via simulated annealing. SMSM is conducted in parallel by default.

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Reference manual

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install.packages("synthACS")

1.4.4 by Alex Whitworth, a month ago


Browse source code at https://github.com/cran/synthACS


Authors: Alex Whitworth [aut, cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp

Depends on acs, data.table

Suggests testthat, sp, leaflet, shiny, knitr, rmarkdown, R.rsp

Linking to Rcpp


See at CRAN