Binary regression: Difference between revisions

Content deleted Content added
move linear probability model from "see also" to a quick description in the text
Line 25:
=== Probabilistic model ===
The simplest direct probabilistic model is the [[logit model]], which models the [[log-odds]] as a linear function of the explanatory variable or variables. The logit model is "simplest" in the sense of [[generalized linear model]]s (GLIM): the log-odds are the natural parameter for the [[exponential family]] of the Bernoulli distribution, and thus it is the simplest to use for computations.
 
Another direct probabilistic model is the [[linear probability model]], which models the probability itself as a linear function of the explanatory variables. A drawback of the linear probability model is that, for some values of the explanatory variables, the model will predict probabilities less than zero or greater than one.
 
==See also ==
*{{sectionlink|Generalized linear model#Binary data}}
*[[Linear probability model]]
*[[Fractional model]]