Package: sport
Type: Package
Title: Sequential Pairwise Online Rating Techniques
Version: 0.2.0
Depends: R (>= 3.0)
Authors@R: person("Dawid", 
                  "Kałędkowski", 
                  email = "dawid.kaledkowski@gmail.com",
                  comment = c(ORCID = "0000-0001-9533-457X"),
                  role = c("aut", "cre"))
Maintainer: Dawid Kałędkowski <dawid.kaledkowski@gmail.com>
Description: Calculates ratings for two-player or 
  multi-player challenges. Methods included in package such as are able to 
  estimate ratings (players strengths) and their evolution in time, also able to 
  predict output of challenge. Algorithms are based on Bayesian Approximation 
  Method, and they don't involve any matrix inversions nor likelihood estimation. 
  Parameters are updated sequentially, and computation doesn't require any 
  additional RAM to make estimation feasible. Additionally, base of the package 
  is written in C++ what makes sport computation even faster. Methods used in the 
  package refers to Mark E. Glickman (1999) 
  <http://www.glicko.net/research/glicko.pdf>; 
  Mark E. Glickman (2001) <doi:10.1080/02664760120059219>; 
  Ruby C. Weng, Chih-Jen Lin (2011) 
  <http://jmlr.csail.mit.edu/papers/volume12/weng11a/weng11a.pdf>; 
  W. Penny, Stephen J. Roberts (1999) <doi:10.1109/IJCNN.1999.832603>.
BugReports: https://github.com/gogonzo/sport/issues
Imports: Rcpp, data.table, ggplot2
LinkingTo: Rcpp
License: GPL-2
Encoding: UTF-8
Language: en-US
URL: https://github.com/gogonzo/sport
LazyData: true
RoxygenNote: 7.0.2
Suggests: dplyr, knitr, lobstr, magrittr, pkgdown, rmarkdown, spelling,
        testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-07 07:15:55 UTC; gonzo
Author: Dawid Kałędkowski [aut, cre] (<https://orcid.org/0000-0001-9533-457X>)
Repository: CRAN
Date/Publication: 2020-01-07 09:10:02 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 08:25:54 UTC; windows
Archs: i386, x64
