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

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>.

Version: 0.1.1
Imports: optimx, ggplot2, stats
Published: 2023-12-07
Author: Yunpeng Zhou [aut, cre], Jinfeng Xu [aut]
Maintainer: Yunpeng Zhou <u3514104 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README NEWS
CRAN checks: BTdecayLasso results


Reference manual: BTdecayLasso.pdf


Package source: BTdecayLasso_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BTdecayLasso_0.1.1.tgz, r-oldrel (arm64): BTdecayLasso_0.1.1.tgz, r-release (x86_64): BTdecayLasso_0.1.1.tgz, r-oldrel (x86_64): BTdecayLasso_0.1.1.tgz
Old sources: BTdecayLasso archive


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