# Uniform Distribution (Continuous)

Evaluate and generate random samples from continuous uniform distribution

Statistics and Machine Learning Toolbox™ offers several ways to work with the 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 distribution-specific functions can accept parameters of multiple uniform distributions.

• Use generic distribution functions (`cdf`, `icdf`, `pdf`, `random`) with a specified distribution name (`'Uniform'`) and parameters.

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

## Objects

 `UniformDistribution` Uniform probability distribution object

## Apps

 Probability Distribution Function Interactive density and distribution plots

## Functions

expand all

#### Create `UniformDistribution` Object

 `makedist` Create probability distribution object

#### Work with `UniformDistribution` Object

 `cdf` Cumulative distribution function `icdf` Inverse cumulative distribution function `iqr` Interquartile range `mean` Mean of probability distribution `median` Median of probability distribution `pdf` Probability density function `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
 `mle` Maximum likelihood estimates
 `disttool` Interactive density and distribution plots `qqplot` Quantile-quantile plot `randtool` Interactive random number generation

## Topics

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.