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mvglmmRank  

Multivariate Generalized Linear Mixed Models for Ranking Sports Teams
View on CRAN: Click here


Download and install mvglmmRank package within the R console
Install from CRAN:
install.packages("mvglmmRank")

Install from Github:
library("remotes")
install_github("cran/mvglmmRank")

Install by package version:
library("remotes")
install_version("mvglmmRank", "1.2-4")



Attach the package and use:
library("mvglmmRank")
Maintained by
Andrew T. Karl
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-07-10
Latest Update: 2023-01-08
Description:
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) , Karl, Yang, and Lohr (2014) , and by Karl (2012) . Karl and Zimmerman use this package to illustrate how the home field effect estimator from a mixed model can be biased under nonrandom scheduling.
How to cite:
Andrew T. Karl (2014). mvglmmRank: Multivariate Generalized Linear Mixed Models for Ranking Sports Teams. R package version 1.2-4, https://cran.r-project.org/web/packages/mvglmmRank. Accessed 01 Sep. 2026.
Previous versions and publish date:
(2026-07-09 06:33), 1.0-2 (2014-07-10 07:34), 1.1-1 (2015-07-19 19:44), 1.1-2 (2015-11-13 08:55), 1.2-1 (2018-04-19 22:53), 1.2-2 (2018-08-24 06:40), 1.2-3 (2023-01-07 01:20), 1.2-4 (2023-01-08 01:20)
Other packages that cited mvglmmRank R package
View mvglmmRank citation profile
Other R packages that mvglmmRank depends, imports, suggests or enhances
Complete documentation for mvglmmRank
Functions, R codes and Examples using the mvglmmRank R package
Some associated functions: NB_cre . NB_mov . N_mov . PB_cre . binary_cre . f2008 . f2009 . f2010 . f2011 . f2012 . game.pred . mvglmmRank-package . mvglmmRank . nba2013 . ncaab2012 . nfl2012 . normal_cre . poisson_cre . 
Some associated R codes: NB_cre.R . PB_cre.R . binary_cre.R . game.pred.R . mvglmmRank.R . normal_cre.R . poisson_cre.R .  Full mvglmmRank package functions and examples
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