Package: TrueSkillThroughTime 0.1.1

TrueSkillThroughTime: Skill Estimation Based on a Single Bayesian Network

Most estimators implemented by the video game industry cannot obtain reliable initial estimates nor guarantee comparability between distant estimates. TrueSkill Through Time solves all these problems by modeling the entire history of activities using a single Bayesian network allowing the information to propagate correctly throughout the system. This algorithm requires only a few iterations to converge, allowing millions of observations to be analyzed using any low-end computer. The core ideas implemented in this project were developed by Dangauthier P, Herbrich R, Minka T, Graepel T (2007). "Trueskill through time: Revisiting the history of chess." <https://dl.acm.org/doi/10.5555/2981562.2981605>.

Authors:Gustavo Landfried [aut, cre]

TrueSkillThroughTime_0.1.1.tar.gz
TrueSkillThroughTime_0.1.1.zip(r-4.5)TrueSkillThroughTime_0.1.1.zip(r-4.4)TrueSkillThroughTime_0.1.1.zip(r-4.3)
TrueSkillThroughTime_0.1.1.tgz(r-4.4-any)TrueSkillThroughTime_0.1.1.tgz(r-4.3-any)
TrueSkillThroughTime_0.1.1.tar.gz(r-4.5-noble)TrueSkillThroughTime_0.1.1.tar.gz(r-4.4-noble)
TrueSkillThroughTime_0.1.1.tgz(r-4.4-emscripten)TrueSkillThroughTime_0.1.1.tgz(r-4.3-emscripten)
TrueSkillThroughTime.pdf |TrueSkillThroughTime.html
TrueSkillThroughTime/json (API)

# Install 'TrueSkillThroughTime' in R:
install.packages('TrueSkillThroughTime', repos = c('https://glandfried.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/glandfried/trueskillthroughtime.r/issues

On CRAN:

3.40 score 5 stars 5 scripts 129 downloads 11 exports 1 dependencies

Last updated 1 months agofrom:3798f3fe8f. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-winOKNov 22 2024
R-4.5-linuxOKNov 22 2024
R-4.4-winOKNov 22 2024
R-4.4-macOKNov 22 2024
R-4.3-winOKNov 22 2024
R-4.3-macOKNov 22 2024

Exports:forgetGameGaussianHistoryisapproxlc_printperformancePiPlayerposteriorsTau

Dependencies:hash

Readme and manuals

Help Manual

Help pageTopics
GameGame posteriors posteriors,Game-method
Gaussian*,Gaussian,Gaussian-method +,Gaussian,Gaussian-method -,Gaussian,Gaussian-method /,Gaussian,Gaussian-method ==,Gaussian,Gaussian-method forget forget,Gaussian,numeric,numeric-method Gaussian isapprox isapprox,Gaussian,Gaussian,numeric-method performance,Player-method Pi Pi,Gaussian-method Tau Tau,Gaussian-method
HistoryHistory History-class
Print list of Gaussian using the python and julia syntaxlc_print
Playerperformance Player