gender: Predict Gender from Names Using Historical Data

Infers state-recorded gender categories from first names and dates of birth using historical datasets. By using these datasets instead of lists of male and female names, this package is able to more accurately infer the gender of a name, and it is able to report the probability that a name was male or female. GUIDELINES: This method must be used cautiously and responsibly. Please be sure to see the guidelines and warnings about usage in the 'README' or the package documentation.

Version: 0.5.3
Depends: R (≥ 3.0.0), utils, stats
Imports: dplyr (≥ 0.4.2), httr (≥ 1.0.0), jsonlite (≥ 0.9.16)
Suggests: genderdata (≥ 0.5.0), ggplot2 (≥ 1.0.0), knitr (≥ 1.11), testthat (≥ 0.10.0), rmarkdown (≥ 0.9.0), covr
Published: 2019-11-09
Author: Lincoln Mullen ORCID iD [aut, cre], Cameron Blevins [ctb], Ben Schmidt [ctb]
Maintainer: Lincoln Mullen <lincoln at lincolnmullen.com>
BugReports: https://github.com/ropensci/gender/issues
License: MIT + file LICENSE
URL: https://github.com/ropensci/gender
NeedsCompilation: no
Citation: gender citation info
Materials: README NEWS
CRAN checks: gender results

Downloads:

Reference manual: gender.pdf
Vignettes: Predicting Gender Using Historical Data
Package source: gender_0.5.3.tar.gz
Windows binaries: r-devel: gender_0.5.3.zip, r-release: gender_0.5.2.zip, r-oldrel: gender_0.5.3.zip
OS X binaries: r-release: gender_0.5.3.tgz, r-oldrel: gender_0.5.3.tgz
Old sources: gender archive

Reverse dependencies:

Reverse imports: qdap

Linking:

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