Sequential Pairwise Online Rating Techniques

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) ; Ruby C. Weng, Chih-Jen Lin (2011) < http://jmlr.csail.mit.edu/papers/volume12/weng11a/weng11a.pdf>; W. Penny, Stephen J. Roberts (1999) .


News

sport v0.1.2 (Release date: 2018-01-07)

Changes:

  • Corrected weight parameter in all functions.

Reference manual

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install.packages("sport")

0.1.2 by Dawid Kałędkowski, 3 months ago


https://github.com/gogonzo/sport


Report a bug at https://github.com/gogonzo/sport/issues


Browse source code at https://github.com/cran/sport


Authors: Dawid Kałędkowski [aut, cre]


Documentation:   PDF Manual  


GPL-2 license


Imports Rcpp, data.table, ggplot2

Suggests dplyr, knitr, magrittr, rmarkdown, testthat

Linking to Rcpp


See at CRAN