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
DOI:	10.32614/CRAN.package.BTdecayLasso
Author:	Yunpeng Zhou [aut, cre], Jinfeng Xu [aut]
Maintainer:	Yunpeng Zhou <u3514104 at connect.hku.hk>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	BTdecayLasso results

Documentation:

Reference manual:

BTdecayLasso.html , BTdecayLasso.pdf

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Package source:	BTdecayLasso_0.1.1.tar.gz
Windows binaries:	r-release: BTdecayLasso_0.1.1.zip, r-oldrel: BTdecayLasso_0.1.1.zip
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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