nfl2012

datasets

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.

Andrew T Karl

mvglmmRank

Multivariate Generalized Linear Mixed Models for Ranking Sports
Teams

Jennifer Broatch

nfl2012 function

A data frame with 256 observations on the following 9 variables.<dl>
 <dt><code>Date</code></dt>
<dd>a factor</dd> <dt><code>away</code></dt>
<dd>a factor</dd>
 
 <dt><code>home</code></dt>
<dd>a factor</dd>
 
 <dt><code>neutral.site</code></dt>
<dd>a numeric vector</dd> <dt><code>home.response</code></dt>
<dd>a numeric vector</dd> <dt><code>home.score</code></dt>
<dd>a numeric vector</dd> <dt><code>away.response</code></dt>
<dd>a numeric vector</dd> <dt><code>away.score</code></dt>
<dd>a numeric vector</dd> <dt><code>partition</code></dt>
<dd>a numeric vector</dd> 
</dl>

Format

2012 NFL Regular Season Data — nfl2012

A data frame with 256 observations on the following 9 variables.<dl>
 <dt><code>Date</code></dt>
<dd>a factor</dd>

 <dt><code>away</code></dt>
<dd>a factor</dd>
 
 <dt><code>home</code></dt>
<dd>a factor</dd>
 
 <dt><code>neutral.site</code></dt>
<dd>a numeric vector</dd>

 <dt><code>home.response</code></dt>
<dd>a numeric vector</dd>

 <dt><code>home.score</code></dt>
<dd>a numeric vector</dd>

 <dt><code>away.response</code></dt>
<dd>a numeric vector</dd>

 <dt><code>away.score</code></dt>
<dd>a numeric vector</dd>

 <dt><code>partition</code></dt>
<dd>a numeric vector</dd>

 
</dl>

nfl2012: 2012 NFL Regular Season Data

Description

Usage

Arguments

Format

Examples