person("Daniel", "Jacob", email="daniel.jacob@inrae.fr", role=c("cre", "aut"), comment=c(ORCID="0000-0002-6687-7169")),
Copyright: Institut national de recherche pour l’agriculture,

Author: Bill Venables <Bill.Venables@cmis.csiro.au>. Ported to R by
Description: The datasets for the exercises in Rnotes.

Ported to R by Brian Ripley <ripley@stats.ox.ac.uk>.

Title: Interface to the Numerai Machine Learning Tournament API
person("Omni Analytics Group", email = "services@omnianalytics.io", role = "aut"),
person("Eric Hare", email = "eric@omnianalytics.io", role = "cre"))
Description: Routines to interact with the Numerai Machine Learning Tournament
API <https://numer.ai>. The functionality includes the ability to automatically download the
current tournament data, submit predictions, and to get information for your
user. General 'GraphQL' queries can also be executed.

Imports: httr, lubridate, dplyr, tidyr, ggplot2, purrr

Imports: httr, lubridate, dplyr, tidyr, ggplot2, purrr, arrow,

person("Omni Analytics Group", email = "lawrence@omnianalytics.org", role = "aut"),
person("Eric Hare", email = "eric@omnianalytics.org", role = "cre"),
person("Yogesh Bansal", email = "yogesh.bansal@live.com", role = "ctb"))
Imports: httr, lubridate, jsonlite, ghql

Title: An Incomplete Wrapper of the 'nvd3' JavaScript Library
person("Stéphane", "Laurent", email = "laurent_step@outlook.fr", role = c("aut", "cre")),
person("Novus Partners, Inc.", role = "cph", comment = "'nvd3.js' library"),
person("Michael", "Bostock", role = "cph", comment = "'d3.js' library")
Description: Creates JavaScript charts with the 'nvd3' library. So far only the multibar chart, the horizontal multibar chart, the line chart and the line chart with focus are available.
Imports: lubridate, data.table, htmlwidgets, lazyeval, viridisLite,
Novus Partners, Inc. [cph] ('nvd3.js' library),

person("Maximilian", "Maier",     role = "aut",
email   = "maximilianmaier0401@gmail.com", comment = c(ORCID = "0000-0002-9873-6096")),
person("Eric-Jan", "Wagenmakers", role = "ths",
person("Joris", "Goosen",         role = "ctb")
Description: A framework for estimating ensembles of meta-analytic models
(assuming either presence or absence of the effect, heterogeneity, and
publication bias) and using Bayesian model averaging to combine them. The
ensembles use Bayes Factors to test for the presence or absence of the
individual components (e.g., effect vs. no effect) and model-averages
parameter estimates based on posterior model probabilities
(Maier, Bartoš & Wagenmakers, 2020, <doi:10.31234/osf.io/u4cns>). The user can
define a wide range of non-informative or informative priors for the
effect size, heterogeneity, and weight functions. The package provides
convenient functions for summary, visualizations, and fit diagnostics.
Imports: runjags, bridgesampling, rjags, coda, psych, stats, graphics,
Suggests: ggplot2, rstan, metaBMA, testthat, vdiffr, knitr, rmarkdown
Packaged: 2020-07-31 14:41:52 UTC; Frantisek
Author: František Bartoš [aut, cre] (<https://orcid.org/0000-0002-0018-5573>),