Title: Ensemble Forecast Verification for Large Data Sets
metrics for (comparative) verification of ensemble forecasts to large data sets.

person("Jonas", "Bhend",  role = c("cre"),
Description: Set of tools to simplify application of atomic forecast
verification metrics for (comparative) verification of ensemble forecasts
to large data sets. The forecast metrics are imported from the
'SpecsVerification' package, and additional forecast metrics are provided
with this package. Alternatively, new user-defined forecast scores can be
implemented using the example scores provided and applied using the
Suggests: testthat, knitr, rmarkdown, parallel, R.rsp, verification

Depends: R (>= 3.0), SpecsVerification (>= 0.4), stats, utils

Depends: R (>= 3.0), SpecsVerification (>= 0.5), stats, utils

Package: easyalluvial
Title: Generate Alluvial Plots with a Single Line of Code
Version: 0.1.7
Authors@R: person( "Bjoern", "Koneswarakantha", role = c("aut","cre"), email = "datistics@gmail.com", comment = c(ORCID = " 0000-0003-4585-7799") )
URL: https://github.com/erblast/easyalluvial
Description: Alluvial plots are similar to sankey diagrams and visualise categorical data
over multiple dimensions as flows. (Rosvall M, Bergstrom CT (2010) Mapping Change in
Large Networks. PLoS ONE 5(1): e8694. <doi:10.1371/journal.pone.0008694>
Their graphical grammar however is a bit more complex then that of a regular x/y
plots. The 'ggalluvial' package made a great job of translating that grammar into
'ggplot2' syntax and gives you many option to tweak the appearance of an alluvial
plot, however there still remains a multi-layered complexity that makes it difficult
to use 'ggalluvial' for explorative data analysis. 'easyalluvial' provides a simple
interface to this package that allows you to produce a decent alluvial plot from any
dataframe in either long or wide format from a single line of code while also handling
continuous data. It is meant to allow a quick visualisation of entire dataframes
with a focus on different colouring options that can make alluvial plots a great
tool for data exploration.
License: CC0
Encoding: UTF-8
LazyData: true
Depends: R(>= 2.10)
Suggests: testthat, covr, ISLR, nycflights13
RoxygenNote: 6.1.1
Imports: purrr , tidyr , dplyr , forcats , ggalluvial , ggplot2 ,
RColorBrewer , recipes , rlang , stringr , magrittr , tibble
Language: en-US
NeedsCompilation: no
Packaged: 2018-12-10 00:19:39 UTC; erbla
Author: Bjoern Koneswarakantha [aut, cre] (<https://orcid.org/
0000-0003-4585-7799>)
Maintainer: Bjoern Koneswarakantha <datistics@gmail.com>
Repository: CRAN
Date/Publication: 2018-12-18 16:50:03 UTC