Logistic Distribution

Fit, evaluate, and generate random samples from logistic distribution

Statistics and Machine Learning Toolbox™ offers multiple ways to work with the logistic distribution.

Create a LogisticDistribution object and use LogisticDistribution object functions.
Use the generic distribution functions with the specified distribution name "Logistic" and corresponding parameters.

To learn about the logistic distribution, see Logistic Distribution.

Functions

`makedist`	Create probability distribution object
`fitdist`	Fit probability distribution object to data
`distributionFitter`	Open Distribution Fitter app

`cdf`	Cumulative distribution function
`gather`	Gather properties of Statistics and Machine Learning Toolbox object from GPU (Since R2020b)
`icdf`	Inverse cumulative distribution function
`iqr`	Interquartile range of probability distribution
`mean`	Mean of probability distribution
`median`	Median of probability distribution
`negloglik`	Negative loglikelihood of probability distribution
`paramci`	Confidence intervals for probability distribution parameters
`pdf`	Probability density function
`plot`	Plot probability distribution object (Since R2022b)
`proflik`	Profile likelihood function for probability distribution
`random`	Random numbers
`std`	Standard deviation of probability distribution
`truncate`	Truncate probability distribution object
`var`	Variance of probability distribution

`cdf`	Cumulative distribution function
`icdf`	Inverse cumulative distribution function
`pdf`	Probability density function
`random`	Random numbers
`mle`	Maximum likelihood estimates

LogisticDistribution Logistic probability distribution object

Logistic Distribution
The logistic distribution is used for growth models and in logistic regression.