The plotup() function also makes it possible to obtain the code used to generate the graphic,

Depends: ggplot2, gridExtra, rmarkdown, glue
Imports: pander, lubridate, tibble, sm, RColorBrewer, forcats, stats,

Imports: pander, lubridate, tibble, sm, RColorBrewer, forcats, GGally

Imports: ggplot2, gridExtra, rmarkdown, glue, pander, lubridate,
tibble, sm, RColorBrewer, forcats, GGally
Suggests: knitr, MASS, hexbin, testthat (>= 2.1.0)

a.) wideplot graphics for exploring the structure of a dataset through a grid of variables
b.) longplot graphics, which present the entire catalog of available graphics for representing
c.) plotup function, which presents a particular graphic for a specific variable of a dataset.
d.) matrixplot graphics that is a grid of a particular graphic showing bivariate relationships
between all pairs of variables of a certain(s) type(s) in a multivariate data set.

Description: Functions to handle basic input output, these functions always
read and write UTF-8 (8-bit Unicode Transformation Format) files and provide
more explicit control over line endings.

Description: Functions to handle basic input output, these functions
always read and write UTF-8 (8-bit Unicode Transformation Format)
files and provide more explicit control over line endings.

Description: An interface to the 'Briq' API <https://briq.github.io>. 'Briq' is
a tool that aims to promote employee engagement by helping employees
recognize and reward each other. Employees can praise and thank one another
(for achieving a company goal, for example) by giving virtual credits (known
as 'briqs' or 'bqs') that can be redeemed for various rewards. The 'Briq'
API lets you create, read, update and delete users, user groups,
transactions and messages. This package provides functions that simplify
getting the users, user groups and transactions of your organization into R.
Suggests: httptest (>= 3.2.2), testthat (>= 2.1.1)
Packaged: 2019-05-14 16:55:26 UTC; david.rubinger

Description: Quantitative methods for benefit-risk analysis help to condense
complex decisions into a univariate metric describing the overall benefit
relative to risk.  One approach is to use the multi-criteria decision
analysis framework (MCDA), as in Mussen, Salek, and Walker
analysis incorporates uncertainty through posterior distributions which are
inputs to the benefit-risk framework.  The brisk package provides functions
to assist with Bayesian benefit-risk analyses, such as MCDA.
Users input posterior samples, utility functions, weights, and the package
outputs quantitative benefit-risk scores.  The posterior of the benefit-risk
scores for each group can be compared.  Some plotting capabilities are also
Imports: dplyr (>= 1.0), ellipsis (>= 0.3), ggplot2 (>= 3.3), hitandrun
Suggests: knitr, fs (>= 1.5), testthat (>= 3.0.0), tibble (>= 3.1),