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BTdecayLasso
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Download and install BTdecayLasso package within the R console
Install from CRAN:
install.packages("BTdecayLasso")
Install from Github:
library("remotes")
install_github("cran/BTdecayLasso")
Install by package version:
library("remotes")
install_version("BTdecayLasso", "0.1.1")
Attach the package and use:
library("BTdecayLasso")
Maintained by
Yunpeng Zhou
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-06-27
Latest Update: 2023-12-07
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) .
How to cite:
Yunpeng Zhou (2018). BTdecayLasso: Bradley-Terry Model with Exponential Time Decayed Log-Likelihood and Adaptive Lasso. R package version 0.1.1, https://cran.r-project.org/web/packages/BTdecayLasso
Previous versions and publish date:
0.1.0 (2018-06-27 16:58)
Other packages that cited BTdecayLasso R package
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Other R packages that BTdecayLasso depends,
imports, suggests or enhances
Functions, R codes and Examples using
the BTdecayLasso R package
Some associated functions: BTdataframe . BTdecay . BTdecayLasso . BTdecayLassoC . BTdecayLassoF . NFL2010 . boot.BTdecayLasso . plot.swlasso . plot.wlasso .
Some associated R codes: BTLagrangian.R . BTLasso.weight.R . BTLikelihood.R . BTLikelihood.all.R . BTdataframe.R . BTdecay.Qua.R . BTdecay.R . BTdecayLasso.R . BTdecayLasso.step1.R . BTdecayLasso.step2.R . BTdecayLassoC.R . BTdecayLassoF.R . BTtheta.R . NFL2010.R . anRpackage-internal.R . bootBTdecayLasso.R . penaltyAmount.R . plot.R . summary.R . Full BTdecayLasso package functions and examples
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