person("Volodymyr", "Trotsiuk", email = "volodymyr.trotsiuk@wsl.ch", role = c("aut", 'cre'), comment=c(ORCID="0000-0002-8363-656X")),

person("David", "Forrester", email = "david.forrester@wsl.ch", role = c("aut")),
person("Ramiro", "Silveyra Gonzalez", email = "ramiro.gonzalez@kit.edu", role = c("aut"), comment=c(ORCID="0000-0002-3430-8383"))

Title: Create Interactive 3D Visualizations of Molecular Data
Description: Create rich and fully interactive 3D visualizations of molecular data.
Visualizations can be included in Shiny apps and R markdown documents, or viewed
from the R console and 'RStudio' Viewer. 'r3dmol' includes an extensive API
to manipulate the visualization after creation, and supports getting data out of
the visualization into R. Based on the '3dmol.js' and the 'htmlwidgets' R package.
Suggests: knitr, rmarkdown, shiny, colourpicker, covr, testthat

Imports: htmlwidgets, magrittr, methods, bio3d

Title: 'WebGL'-Based 3D Plotting using the 'three.js' Library
Description: Provides R and 'JavaScript' functions to allow 'WebGL'-based 3D plotting
using the 'three.js' 'JavaScript' library. Interactivity through roll-over
highlighting and toggle buttons is also supported.
Imports: htmlwidgets, htmltools, jsonlite, ellipsis, vctrs
Suggests: testthat, rmarkdown, colorspace, knitr

person("Johannes", "Burkhardt", ,"banboodata@gmail.com", role = c("aut","cre")
person("Matthias", "Bannert", ,"banboodata@gmail.com", role = c("aut")
Description: Interface for the 'Google Ads API'. 'Google Ads' is an online
advertising service that enables advertisers to display advertising to web
users (see <https://developers.google.com/google-ads/> for more information).
Packaged: 2022-02-28 11:18:09 UTC; jburkhardt

Packaged: 2022-02-24 12:36:06 UTC; jburkhardt

Package: r4lineups
Title: Statistical Inference on Lineup Fairness
Version: 0.1.1
Authors@R: c(
person("Colin", "Tredoux", email = "colin.tredoux@uct.ac.za", role = c("aut", "cre")),
person("Tamsyn", "Naylor", email = "tmnaylor@outlook.com", role = "aut"))
Maintainer: Colin Tredoux <colin.tredoux@uct.ac.za>
Description: Since the early 1970s eyewitness testimony researchers have recognised the
importance of estimating properties such as lineup bias (is the lineup biased against
the suspect, leading to a rate of choosing higher than one would expect by chance?),
and lineup size (how many reasonable choices are in fact available to the witness?
A lineup is supposed to consist of a suspect and a number of additional members,
or foils, whom a poor-quality witness might mistake for the perpetrator). Lineup
measures are descriptive, in the first instance, but since the earliest articles in
the literature researchers have recognised the importance of reasoning inferentially
about them. This package contains functions to compute various properties of
laboratory or police lineups, and is intended for use by researchers in forensic
psychology and/or eyewitness testimony research. Among others, the r4lineups package
includes functions for calculating lineup proportion, functional size, various
estimates of effective size, diagnosticity ratio, homogeneity of the diagnosticity
ratio, ROC curves for confidence x accuracy data and the degree of similarity of
faces in a lineup.
Depends: R (>= 3.4.0)
Imports: boot, dplyr, ggplot2, ggrepel, here, magick, magrittr, pROC,
psych, purrr, stats, utils
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1.9000
Suggests: knitr, rmarkdown, pander
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-07-12 07:42:53 UTC; Tamsyn Naylor
Author: Colin Tredoux [aut, cre],
Tamsyn Naylor [aut]
Repository: CRAN
Date/Publication: 2018-07-18 13:20:02 UTC