plyr, dplyr (>= 1.0.4), stringr (>= 1.4.0), readr (>= 1.4.0),
tibble (>= 3.0.6), haven, xml2, data.table, RCurl, DT
knitr, rmarkdown, devtools, plotly, ggplot2 (>= 3.3.3),
shiny, tidyr, curl

plyr, dplyr (>= 1.0.4), stringr (>= 1.4.0), readr (>= 1.4.0),
tibble (>= 3.0.6), tidyr, haven, xml2, data.table, RCurl, DT
knitr, rmarkdown, devtools, plotly, ggplot2 (>= 3.3.3),
shiny, curl

c(	person("ILO Department of Statistics", role = c("cph", "fnd"), email = "ilostat@ilo.org"),
person("David Bescond", role = c("aut", "cre"), email = "bescond@ilo.org",
comment = c(ORCID = "0000-0002-1642-0304")),
person("Mabelin Villarreal-Fuentes", role = c("ctb"), email = "villarreal-fuentes@ilo.org")
)
ILO Department of Statistics [cph, fnd],
David Bescond [aut, cre] (<https://orcid.org/0000-0002-1642-0304>),
Mabelin Villarreal-Fuentes [ctb]

An Implementation of the 'Instagram' API Using Tidy Principles
Provides functions to use the 'Instagram' API to get feed and user
information, but also performs basic in-app functionality such as liking,
commenting, following, and blocking. Use of this package means that you will
not use it to spam, harass, or perform other nefarious acts. For more details
on how to use the API please see this package's website
<https://eric88tchong.github.io/Rinstapkg/> for more information, documentation,
and examples.
c(
person("Eric", "Tchong", , "est2fr@virginia.edu", c("aut", "cre")),
person(c("Steven", "M."), "Mortimer", , "reportmort@gmail.com", c("ctb")),
person("Jennifer", "Bryan", , "jenny@rstudio.com", c("ctb", "cph")),
person("Joanna", "Zhao", , "joanna.zhao@alumni.ubc.ca", c("ctb", "cph"))
)
methods, httr, dplyr, jsonlite, purrr, readr, lubridate,
digest, uuid, rlang
Eric Tchong [aut, cre],
Steven M. Mortimer [ctb],
Jennifer Bryan [ctb, cph],
Joanna Zhao [ctb, cph]

Utility functions and S3 classes for IPv4 and IPv6 addresses, including
conversion to and from binary representation.

Parameter estimation, computation of probability, information, and
(log-)likelihood, and visualization of item/test characteristic curves and
item/test information functions for three uni-dimensional item response theory
models: the 3-parameter-logistic model, generalized partial credit model,
and graded response model. The full documentation and tutorials are at
<https://github.com/xluo11/Rirt>.