Title: Generate and modify synthetic datasets
Description: Set of functions to create datasets using a correlation matrix.

Title: Generate and Modify Synthetic Datasets

Title: Gender: predict gender from names using historical data
Authors@R: c(person("Lincoln", "Mullen", role = c("aut", "cre"),
person("Cameron", "Blevins", role = "ctb"),
Description: Encodes gender based on names and dates of birth, using either the
Social Security Administration's data set of first names by year of birth
or Census Bureau data from 1789 to 1940, both from the United States of
America. By using these data sets instead of lists of male and female names,
this package is able to more accurately guess the gender of a name, and it
is able to report the probability that a name was male or female.
Imports: devtools(>= 1.5), dplyr (>= 0.2), httr (>= 0.4), jsonlite (>=
Suggests: ggplot2, knitr, magrittr, testthat

Title: Predict Gender from Names Using Historical Data
or the Census Bureau data from 1789 to 1940, both from the United States of

Description: Encodes gender based on names and dates of birth using historical
datasets. By using these datasets instead of lists of male and female names,

testthat (>= 0.10.0), rmarkdown (>= 0.9.0), covr

Description: Infers state-recorded gender categories from first names and dates of birth using historical
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.

See Blevins and Mullen (2015) <http://www.digitalhumanities.org/dhq/vol/9/3/000223/000223.html>.
testthat (>= 2.3.2), rmarkdown (>= 2.1), covr

Title: Predict Gender from Brazilian First Names
Description: A method to predict and report gender from Brazilian first names
using the Brazilian Institute of Geography and Statistics' Census data.
Imports: dplyr (>= 0.5.0), jsonlite, httr