Logistic distribution

Revision as of 16:54, 5 August 2009 by Lchrisman (talk | contribs)


Logistic Distribution.jpg

Logistic( mean, scale )

The logistic distribution describes a distribution with a cumulative density given by

Logistic cdf eq.PNG

The distribution is symmetric and unimodal with tails that are heavier than the normal distribution. It has a mean and mode of «mean», variance of pi^2 «scale»^2 / 3, kurtosis of 6/5 and zero skew. The «scale» parameter is optional and defaults to 1.

The logistic distribution is particularly convenient for determining dependent probabilities using linear regression techniques, where the probability of a binomial event depends monotonically on a continuous variable x. For example, in a toxicology assay, x may be the dosage of a toxin, and p(x) the probability of death for an animal exposed to that dosage. Using p(x) = F(x), the logit of p, given by

Logit(p(x)) = Ln( p(x) / (1-p(x)) ) = x/s - m/s

has a simple linear form. This linear form lends itself to linear regression techniques for estimating the distribution — for example, from clinical trial data.

Parameter Estimation

The parameters of the distribution can be estimated using:

«mean» := Mean(X,I)
«scale» := Sqrt(3 * Variance(X,I)) / Pi

See Also

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