Decoupled (e.g. separate averages) and censored (e.g. > 100 species) variables are continually reported by many well-established organizations, such as the World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), and World Bank. The challenge therefore is to infer what the original data could have been given summarized information. We present an R package that reverse engineers censored and/or decoupled data with two main functions. The cnbinom.pars() function estimates the average and dispersion parameter of a censored univariate frequency table. The rec() function reverse engineers summarized data into an uncensored bivariate table of probabilities.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2018-044.zip
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For attribution, please cite this work as
Duchscherer, et al., "The R Journal: revengc: An R package to Reverse Engineer Summarized Data", The R Journal, 2018
BibTeX citation
@article{RJ-2018-044,
author = {Duchscherer, Samantha and Stewart, Robert and Urban, Marie},
title = {The R Journal: revengc: An R package to Reverse Engineer Summarized Data},
journal = {The R Journal},
year = {2018},
note = {https://doi.org/10.32614/RJ-2018-044},
doi = {10.32614/RJ-2018-044},
volume = {10},
issue = {2},
issn = {2073-4859},
pages = {114-123}
}