Logistic probability distribution object
LogisticDistribution object consists of parameters, a
model description, and sample data for a logistic probability
The logistic distribution is used for growth models and in logistic regression. It has longer tails and a higher kurtosis than the normal distribution.
The logistic distribution uses the following parameters.
There are several ways to create a
Mean of the logistic distribution, specified as a scalar value.
sigma— Scale parameter
Scale parameter of the logistic distribution, specified as a nonnegative scalar value.
|Cumulative distribution function|
|Gather properties of Statistics and Machine Learning Toolbox object from GPU|
|Inverse cumulative distribution function|
|Mean of probability distribution|
|Median of probability distribution|
|Negative loglikelihood of probability distribution|
|Confidence intervals for probability distribution parameters|
|Probability density function|
|Profile likelihood function for probability distribution|
|Standard deviation of probability distribution|
|Truncate probability distribution object|
|Variance of probability distribution|
Create a logistic distribution object using the default parameter values.
pd = makedist('Logistic')
pd = LogisticDistribution Logistic distribution mu = 0 sigma = 1
Create a logistic distribution object by specifying parameter values.
pd = makedist('Logistic','mu',2,'sigma',4)
pd = LogisticDistribution Logistic distribution mu = 2 sigma = 4
Compute the standard deviation of the distribution.
s = std(pd)
s = 7.2552
Usage notes and limitations:
LogisticDistribution can be a probability distribution object
fitted by using
fitdist with GPU
array input arguments.
The object functions of
LogisticDistribution fully support GPU
For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).