Imports: Rcpp (>= 1.0.0), methods, stats

Title: Importing and Working with Track and Field Data
Description: Primarily used to convert human readable track and field results into dataframes for further analysis.  Results can come from central repositories like <https://www.flashresults.com/> or <http://www.deltatiming.com/>, or from individual team sites, like those for colleges.   Also contains functions useful for working with track and field data.
Imports: magrittr, dplyr, purrr, pdftools, rvest, stringr, SwimmeR,
Author: Greg Pilgrim [aut, cre] (<https://orcid.org/0000-0001-7831-442X>),

person("Spencer Aiello",   role=c("aut", "cre", "cph"), email="spnrpa@gmail.com"),
person("RStudio (Hadley Wickham)", role="cph") )
Imports: utils, jsonlite, repr, Rcpp (>= 0.11.0), gdtools (>= 0.1.6),
Collate: 'booter.R' 'comm_close.R' 'comm_info_request.R' 'comm_msg.R'
Description: Provides a full implementation of the 'Jupyter' <http://jupyter.org/> messaging protocol in C++ by leveraging 'Rcpp' and 'Xeus' <https://github.com/QuantStack/xeus>.
'Jupyter' supplies an interactive computing environment and a messaging protocol defined over 'ZeroMQ' for multiple programming languages. This package implements
the 'Jupyter' kernel interface so that 'R' is exposed to this interactive computing environment.
'Xeus' is a C++ library that facilitates the implementation of kernels for 'Jupyter'. Additionally, 'Xeus' provides an interface to libraries that exist in the 'Jupyter' ecosystem for building widgets,
plotting, and more <https://blog.jupyter.org/interactive-workflows-for-c-with-jupyter-fe9b54227d92>. 'JuniperKernel' uses 'Xeus' as a library for the 'Jupyter' messaging protocol.

pbdZMQ (>= 0.3-0), data.table, methods, subprocess
the 'Jupyter' kernel interface so that 'R' is exposed to this interactive computing environment. 'ZeroMQ' functionality is provided by the 'pbdZMQ' package.

Title: Justifying Alpha Levels for Hypothesis Tests
Description: Functions to justify alpha levels for statistical hypothesis tests by avoiding Lindley's paradox, or by minimizing or balancing error rates. For more information about the package please read the following: Maier & Lakens (2021) <doi:10.31234/osf.io/ts4r6>).
Imports: stats, BayesFactor, ggplot2, stringr, shiny, Superpower, pwr,
Packaged: 2021-09-13 19:34:27 UTC; Maximilian Maier