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markhwhiteii
bwsTools:Tools for Case 1 Best-Worst Scaling (MaxDiff) Designs
Tools to design best-worst scaling designs (i.e., balanced incomplete block designs) and to analyze data from these designs, using aggregate and individual methods such as: difference scores, Louviere, Lings, Islam, Gudergan, & Flynn (2013) <doi:10.1016/j.ijresmar.2012.10.002>; analytical estimation, Lipovetsky & Conklin (2014) <doi:10.1016/j.jocm.2014.02.001>; empirical Bayes, Lipovetsky & Conklin (2015) <doi:10.1142/S1793536915500028>; Elo, Hollis (2018) <doi:10.3758/s13428-017-0898-2>; and network-based measures.
Maintained by Mark White. Last updated 4 years ago.
13 stars 5.72 score 27 scripts
echasnovski
comperank:Ranking Methods for Competition Results
Compute ranking and rating based on competition results. Methods of different nature are implemented: with fixed Head-to-Head structure, with variable Head-to-Head structure and with iterative nature. All algorithms are taken from the book 'Who’s #1?: The science of rating and ranking' by Amy N. Langville and Carl D. Meyer (2012, ISBN:978-0-691-15422-0).
Maintained by Evgeni Chasnovski. Last updated 2 years ago.
24 stars 5.65 score 37 scripts
cran
PlayerRatings:Dynamic Updating Methods for Player Ratings Estimation
Implements schemes for estimating player or team skill based on dynamic updating. Implemented methods include Elo, Glicko, Glicko-2 and Stephenson. Contains pdf documentation of a reproducible analysis using approximately two million chess matches. Also contains an Elo based method for multi-player games where the result is a placing or a score. This includes zero-sum games such as poker and mahjong.
Maintained by Alec Stephenson. Last updated 5 years ago.
9 stars 3.43 score