title: Can multinomial models be estimated using Generalized Linear model?
body: <p>In analysis of categorical data, we often use logistic regression to estimate relationships between binomial outcomes and one or more covariates. </p>
  
  <p>I understand this is a type of generalized linear model (GLM). In R, this is implemented with the <code>glm</code> function using the argument <code>family=binomial</code>. On the other hand, in categorical data analysis are multinomial models. Are these not GLMs? And can't they be estimated in R using the <code>glm</code> function?</p>
  
  <p>(In this <a href="http://www.ats.ucla.edu/stat/r/dae/mlogit.htm" rel="noreferrer">post for Multinomial Logistic Regression</a>. The author uses an external package <code>mlogit</code>, which seems also outdated)</p>
  
  <p>Why is the class of GLMs restricted to dichotomous outcomes? Is it because multi-class classification can be treated as multiple binary classification models? </p>