Package: BTdecayLasso 0.1.1
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>.
Authors:
BTdecayLasso_0.1.1.tar.gz
BTdecayLasso_0.1.1.zip(r-4.7)BTdecayLasso_0.1.1.zip(r-4.6)BTdecayLasso_0.1.1.zip(r-4.5)
BTdecayLasso_0.1.1.tgz(r-4.6-any)BTdecayLasso_0.1.1.tgz(r-4.5-any)
BTdecayLasso_0.1.1.tar.gz(r-4.7-any)BTdecayLasso_0.1.1.tar.gz(r-4.6-any)
BTdecayLasso_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BTdecayLasso/json (API)
NEWS
| # Install 'BTdecayLasso' in R: |
| install.packages('BTdecayLasso', repos = c('https://heilokchow.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/heilokchow/btdecaylasso/issues
- NFL2010 - The 2010 NFL Regular Season
Last updated from:7c037086fa. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 178 | ||
| source / vignettes | OK | 163 | ||
| linux-release-x86_64 | OK | 122 | ||
| macos-release-arm64 | OK | 106 | ||
| macos-oldrel-arm64 | OK | 99 | ||
| windows-devel | OK | 82 | ||
| windows-release | OK | 78 | ||
| windows-oldrel | OK | 87 | ||
| wasm-release | OK | 98 |
Exports:boot.BTdecayLassoBTdataframeBTdecayBTdecayLassoBTdecayLassoCBTdecayLassoF
Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecyclenloptrnumDerivoptimxpracmaR6RColorBrewerrlangS7scalesvctrsviridisLitewithr
