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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 |
Maintainer: | Andrew T. Karl <akarl at asu.edu> |
License: | GPL-2 |
NeedsCompilation: | no |
Materials: | NEWS |
In views: | MixedModels, SportsAnalytics |
CRAN checks: | mvglmmRank results |
Reference manual: | mvglmmRank.pdf |
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 |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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