Uniform Distribution (Continuous)

Evaluate and generate random samples from continuous uniform distribution

Statistics and Machine Learning Toolbox™ offers several ways to work with the continuous uniform distribution.

Create a probability distribution object UniformDistribution by specifying parameter values. Then, use object functions to evaluate the distribution, generate random numbers, and so on.
Use distribution-specific functions with specified distribution parameters. The functions can accept parameters of multiple uniform distributions.
Use the generic distribution functions with the specified distribution name "Uniform" and corresponding parameters.

To learn about the uniform distribution, see Uniform Distribution (Continuous).

Objects

UniformDistribution Uniform probability distribution object

makedist Create probability distribution object

`cdf`	Cumulative distribution function
`icdf`	Inverse cumulative distribution function
`iqr`	Interquartile range of probability distribution
`mean`	Mean of probability distribution
`median`	Median of probability distribution
`pdf`	Probability density function
`plot`	Plot probability distribution object (Since R2022b)
`random`	Random numbers
`std`	Standard deviation of probability distribution
`truncate`	Truncate probability distribution object
`var`	Variance of probability distribution

`rand`	Uniformly distributed random numbers
`unifcdf`	Continuous uniform cumulative distribution function
`unifpdf`	Continuous uniform probability density function
`unifinv`	Continuous uniform inverse cumulative distribution function
`unifit`	Continuous uniform parameter estimates
`unifstat`	Continuous uniform mean and variance
`unifrnd`	Continuous uniform random numbers

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

`Probability Distribution Function Tool`	Interactive density and distribution plots
`plot`	Plot probability distribution object (Since R2022b)
`qqplot`	Quantile-quantile plot
`randtool`	Interactive random number generation

Uniform Distribution (Continuous)
The uniform distribution (also called the rectangular distribution) is notable because it has a constant probability distribution function between its two bounding parameters.
Generate Random Numbers Using Uniform Distribution Inversion
This example shows how to generate random numbers using the uniform distribution inversion method.