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

Functions

expand all

`UniformDistribution` Object Functions

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

Distribution-Specific Functions

`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

Maximum Likelihood Estimation

mle Maximum likelihood estimates

Distribution Plots

`disttool`	Interactive density and distribution plots
Probability Distribution Function	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.