mvglmmRank
Multivariate Generalized Linear Mixed Models for Ranking Sports Teams
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2-4 |
rolling source/ R- | mvglmmRank_1.2-4.tar.gz |
149.4 KiB |
1.2-4 |
rolling linux/jammy R-4.5 | mvglmmRank_1.2-4.tar.gz |
396.2 KiB |
1.2-4 |
rolling linux/noble R-4.5 | mvglmmRank_1.2-4.tar.gz |
396.7 KiB |
1.2-4 |
latest source/ R- | mvglmmRank_1.2-4.tar.gz |
149.4 KiB |
1.2-4 |
latest linux/jammy R-4.5 | mvglmmRank_1.2-4.tar.gz |
396.2 KiB |
1.2-4 |
latest linux/noble R-4.5 | mvglmmRank_1.2-4.tar.gz |
396.7 KiB |
1.2-4 |
2026-04-23 source/ R- | mvglmmRank_1.2-4.tar.gz |
149.4 KiB |
1.2-4 |
2026-04-09 windows/windows R-4.5 | mvglmmRank_1.2-4.zip |
399.0 KiB |
1.2-4 |
2025-04-20 source/ R- | mvglmmRank_1.2-4.tar.gz |
149.4 KiB |