Details for the logistic distribution are given by Stephens (1979).
In the logit model we assume that y follows a logistic distribution.
Normal and logistic distributions are easy to work with using numerical methods.
This is useful because the difference of two Gumbel-distributed random variables has a logistic distribution.
The probability density function (pdf) of the logistic distribution is given by:
Indeed, the logistic and normal distributions have a quite similar shape.
The term generalized logistic distribution is used as the name for several different families of probability distributions.
The unobserved term, ε, is assumed to have a logistic distribution.
Significant statistical anomalies have also been found when using the logistic distribution in chess.
When 0, the shifted log-logistic reduces to the logistic distribution.