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BTdecayLasso

Bradley-Terry Model with Exponential Time Decayed Log-Likelihood and Adaptive Lasso

v0.1.1 · Dec 7, 2023 · GPL (>= 2)

Description

We utilize the Bradley-Terry Model to estimate the abilities of teams using paired comparison data. For dynamic approximation of current rankings, we employ the Exponential Decayed Log-likelihood function, and we also apply the Lasso penalty for variance reduction and grouping. The main algorithm applies the Augmented Lagrangian Method described by Masarotto and Varin (2012) <doi:10.1214/12-AOAS581>.

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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
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r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
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r-release-macos-arm64 OK
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r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies optimx ggplot2 BTdecayLasso

Version History

new 0.1.1 Mar 10, 2026
updated 0.1.1 ← 0.1.0 diff Dec 6, 2023
new 0.1.0 Jun 26, 2018