footballscores

Game outcomes and point spreads for 672 professional
American football games.

datasets

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference.  It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions.  It contains MCMC algorithms for summarizing posterior distributions defined by the user.  It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Jim Albert

LearnBayes

Functions for Learning Bayesian Inference

footballscores function

A data frame with 672 observations on the following 8 variables.<dl class="dl-horizontal">
 <dt>year</dt><dd>year of game</dd>
 <dt>home</dt><dd>indicates if favorite is the home team</dd>
 <dt>favorite</dt><dd>score of favorite team</dd>
 <dt>underdog</dt><dd>score of underdog team</dd>
 <dt>spread</dt><dd>point spread</dd>
 <dt>favorite.name</dt><dd>name of favorite team</dd>
 <dt>underdog.name</dt><dd>name of underdog team</dd>
 <dt>week</dt><dd>week number of the season</dd>
 </dl>

Format

Game outcomes and point spreads for American football — footballscores

A data frame with 672 observations on the following 8 variables.<dl class='dl-horizontal'>
 <dt>year</dt><dd>year of game</dd>
 <dt>home</dt><dd>indicates if favorite is the home team</dd>
 <dt>favorite</dt><dd>score of favorite team</dd>
 <dt>underdog</dt><dd>score of underdog team</dd>
 <dt>spread</dt><dd>point spread</dd>
 <dt>favorite.name</dt><dd>name of favorite team</dd>
 <dt>underdog.name</dt><dd>name of underdog team</dd>
 <dt>week</dt><dd>week number of the season</dd>
 </dl>

footballscores: Game outcomes and point spreads for American football

Description

Usage

Arguments

Format