Depends: R (>= 3.1.0), randomForestSRC (>= 1.5.5)
Imports: randomForest, ggplot2, survival, parallel, tidyr

Depends: R (>= 3.5.0), randomForestSRC (>= 1.5.5)
Imports: ggplot2, survival, parallel, tidyr, randomForest,

Depends: R (>= 3.5.0), randomForestSRC (>= 1.5.5), randomForest
Imports: survival, parallel, tidyr, ggplot2
Suggests: testthat, rmdformats, bookdown, RColorBrewer, MASS, dplyr,
knitr, rmarkdown, plot3D, lintr, datasets

Title: Panels and Interactive Versions of Diagnostic Plots using
Authors@R: c(person("Katherine", "Goode", email = "kgoode@iastate.edu", role = c("aut", "cre")),
person("Kathleen", "Rey", email = "kprey@iastate.edu", role = c("aut")))
Description: An R package for creating panels of diagnostic plots for residuals from a model
using ggplot2 and plotly to analyze residuals and model assumptions from a variety of
viewpoints. It also allows for the creation of interactive diagnostic plots.
Imports: cowplot, ggplot2, grDevices, grid, MASS, plotly, qqplotr,
Suggests: dplyr, forcats, knitr, lme4, lmerTest, nlme, randomForest,
rmarkdown, rpart, testthat, vdiffr, wesanderson

Title: Add-in to Customize 'ggplot2' Themes
Description: Rstudio add-in that delivers a graphical interface for editing 'ggplot2' theme elements.

Title: Time Series Visualisations Using the Grammar of Graphics
person(given = "Aditya", family = "Kothari", email = "aditya.kothari@atherenergy.com", role = c("aut","cre")),
person(given = "Ather", family = "Energy", email = "info@atherenergy.com", role = "cph"),
person(given = "Jesse", family = "Vent", email = "cryptopackage@icloud.com", role = "ctb", comment="Ensuring the package met CRAN requirements")
Description: Provides additional display mediums for time series visualisations, such as calendar heat map, steamgraph, marimekko, etc.
Suggests: knitr, rmarkdown, ggthemes, prettydoc
Jesse Vent [ctb] (Ensuring the package met CRAN requirements)

person("Aditya", "Kothari", , "mail.thecomeonman@gmail.com", role = c("cre","aut")),
Description: Provides additional display mediums for time series visualisations.