mvglmmRank: Multivariate Generalized Linear Mixed Models for Ranking SportsTeams
Maximum likelihood estimates are obtained via an EM algorithm with either a first-order or a fully exponential Laplace approximation as documented by Broatch and Karl (2018) <doi:10.48550/arXiv.1710.05284>, Karl, Yang, and Lohr (2014) <doi:10.1016/j.csda.2013.11.019>, and by Karl (2012) <doi:10.1515/1559-0410.1471>. Karl and Zimmerman <doi:10.1016/j.jspi.2020.06.004> use this package to illustrate how the home field effect estimator from a mixed model can be biased under nonrandom scheduling.
| Version: | 1.2-4 |
| Depends: | R (≥ 3.2.0),Matrix |
| Imports: | numDeriv, methods, stats, utils,MASS |
| Published: | 2023-01-08 |
| DOI: | 10.32614/CRAN.package.mvglmmRank |
| Author: | Andrew T. Karl [cre, aut], Jennifer Broatch [aut] |
| Maintainer: | Andrew T. Karl <akarl at asu.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| In views: | MixedModels,SportsAnalytics |
| CRAN checks: | mvglmmRank results |
Documentation:
| Reference manual: | mvglmmRank.html ,mvglmmRank.pdf |
Downloads:
| Package source: | mvglmmRank_1.2-4.tar.gz |
| Windows binaries: | r-devel:mvglmmRank_1.2-4.zip, r-release:mvglmmRank_1.2-4.zip, r-oldrel:mvglmmRank_1.2-4.zip |
| macOS binaries: | r-release (arm64):mvglmmRank_1.2-4.tgz, r-oldrel (arm64):mvglmmRank_1.2-4.tgz, r-release (x86_64):mvglmmRank_1.2-4.tgz, r-oldrel (x86_64):mvglmmRank_1.2-4.tgz |
| Old sources: | mvglmmRank archive |
Linking:
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