Imports: htmlTable, scales, dplyr, lazyeval (>= 0.2.0), knitr,
Suggests: shiny, testthat (>= 1.0), xlsx (>= 0.5.7), rJava

Imports: htmlTable (>= 1.9), htmltools, tibble, scales, dplyr, lazyeval
(>= 0.2.0), knitr, rmarkdown (>= 0.9.6), gplots, utils

(>= 0.2.0), knitr, rmarkdown (>= 0.9.6), gplots, magrittr,

Imports: grDevices, graphics, gridExtra (>= 2.3), gtable (>= 0.2.0),
Suggests: promises, shiny (>= 1.0.5), testthat (>= 1.0), xlsx (>=

Suggests: promises, shiny (>= 1.0.5), testthat (>= 1.0)

Title: Computation of P Values and Bayes Factors for Conditioning Data
Description: Set of functions for the easy analyses of conditioning data.
Packaged: 2017-02-15 10:44:24 UTC; angelos-miltiadiskrypotos

Packaged: 2020-03-06 12:33:58 UTC; angeloskrypotos

Packaged: 2020-12-01 11:48:29 UTC; angeloskrypotos

Description: Implements specialized conditions, i.e., typed errors,
warnings and messages. Offers a set of standardized conditions (value error,
deprecated warning, io message, ...) in the fashion of Python's built-in

Title: Control How Many Times Conditions are Thrown
Description: Provides ability to control how many times in function
calls conditions are thrown (shown to the user). Includes control of
X-schema.org-keywords: condition, condition-control, warning, message

Title: Conditional Density Estimation with Neural Network Conditional
Description: Conditional density estimation with mixtures for

Description: Neural network conditional mixtures are mixture models whose parameters are predicted by a neural network. The mixture model can thus change its parameters in response to changes in predictive covariates. Mixtures included are gaussian, log-normal and hybrid Pareto mixtures. The latter relies on the generalized Pareto distribution to account for the presence of large extreme events. The unconditional mixtures are also available.

Title: Create Tours in 'Shiny' Apps Using 'Shepherd.js'
Description: Enable the use of 'Shepherd.js' to create tours in 'Shiny'

Title: Query-Driven Pipeline Execution and Query Templates
Description: Runs a function iteratively over each row of either a dataframe
or the results of a query.  Use the 'BigQuery' and 'DBI' wrappers to
iteratively pass each row of query results to a function.  If a field
contains a 'JSON' string, it will be converted to an object.  This is
helpful for queries that return 'JSON' strings that represent objects.
These fields can then be treated as objects by the pipeline.
Suggests: knitr, rmarkdown, whisker, testthat, RSQLite
Depends: R (>= 3.3.2), jsonlite, assertthat, bigrquery, DBI
Packaged: 2017-11-08 09:40:38 UTC; rstevenson