logistic distribution

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.