The Logistic distribution is an unbounded continuous distribution which is symmetrical about its mean [and shift parameter], alpha. The shape of the Logistic distribution is very much like the Normal distribution, except that the Logistic distribution has broader tails.
The Logistic function is most often used a growth model: for populations, for weight gain, for business failure, etc. The Logistic distribution can be can be used to test for the suitability of such a model, with transformation to get back to the minimum and maximum values for the Logistic function. Occasionally, the Logistic function is used in place of the Normal function where exceptional cases play a larger role.(see Johnson et. al.1)
beta = 1; alpha = 0
- Description
- Generates a sample of the Logistic distribution.
- Parameters
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Name Type of value Description beta double The scale parameter > 0. alpha double The shift parameter. - Result
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Type Description double The generated sample.
- Description
- Generates a sample of the Logistic distribution using the specified random number generator.
- Parameters
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Name Type of value Description beta double The scale parameter > 0. alpha double The shift parameter. r java.util.Random The random number generator. - Result
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Type Description double The generated sample.
This document includes content from the “Stat::Fit User’s Manual”. Copyright 2016 Geer Mountain Software Corp.
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