person(given = "Gaston", family = "Sanchez", role="ctb")
Author: Michael Friendly [aut, cre], John Fox [ctb], Georges Monette [ctb], Gaston Sanchez [ctb]
Suggests: MASS, knitr, rglwidget, rmarkdown

person(given = "John", family = "Fox", role="aut"),
Author: Michael Friendly [aut, cre], John Fox [aut], Georges Monette [ctb], Gaston Sanchez [ctb]
to show or demonstrate an algorithm. In addition, a collection of functions are
provided for drawing vector diagrams in 2D and 3D.
Suggests: MASS, knitr, rglwidget, rmarkdown, car

person(given = "Gaston", family = "Sanchez", role="ctb"),
person(given = "Phil", family = "Chalmers", role="ctb")
Author: Michael Friendly [aut, cre], John Fox [aut], Georges Monette [ctb], Gaston Sanchez [ctb], Phil Chalmers [ctb]
Suggests: MASS, knitr, rglwidget, rmarkdown, xtable

person(given = "Phil", family = "Chalmers", role="aut"),
Suggests: knitr, rglwidget, rmarkdown, carData
Imports: xtable, MASS, rgl, car, methods

Authors@R: c(person(given = "Michael", family = "Friendly", role=c("aut", "cre"), email="friendly@yorku.ca",

Suggests: knitr, rglwidget, rmarkdown, carData, webshot2, markdown

person("Leon", "Binder", email = "leon.binder@th-deg.de", role = c("cre", "aut")),
person("Bernhard", "Bauer", email = "bernhard.bauer@th-deg.de", role = "aut"),
person("Michael", "Scholz", email = "michael.scholz@th-deg.de", role = "aut"))
Description: A set of functions, classes and methods for performing ABC and ABC/XYZ analyses, identifying overperforming, underperforming and constantly performing items, and plotting, analyzing as well as predicting the temporal development of items.
Depends: R (>= 3.5.0), graphics, stats, utils, dplyr, tidyr, forecast,

Imports: methods, graphics, stats, utils, data.table, dplyr, tidyr,
tidyverse, plotly, DT, shinydashboard, shinyWidgets, forecast,

tidyselect, plotly, DT, shinydashboard, shinyWidgets, forecast,

Description: A general framework for computing powers of matrices.  A
key feature is the capability for users to write callback functions,
called after each iteration, thus enabling customization for specific
applications.  Diverse types of matrix classes/matrix multiplication
are accommodated.  If the multiplication type computes in parallel,
then the package computation is also parallel.