Pearson Distribution

Evaluate Pearson distribution probability functions and generate random samples

Statistics and Machine Learning Toolbox™ offers two ways to work with the Pearson distribution:

Use distribution-specific functions (pearspdf, pearscdf, pearsrnd) with specified distribution parameters. The distribution-specific functions can accept parameters from multiple Pearson distributions.
Use generic distribution functions (cdf, pdf, random) with the distribution name "Pearson" and specified distribution parameters.

To learn about the Pearson distribution, see Pearson Distribution.

Functions

`pearspdf`	Pearson probability density function (Since R2023b)
`pearscdf`	Pearson cumulative distribution function (Since R2023b)
`pearsrnd`	Pearson system random numbers
`pdf`	Probability density function
`cdf`	Cumulative distribution function
`random`	Random numbers

Topics

Pearson Distribution
The Pearson distribution is a flexible, four-parameter distribution that has an arbitrary mean, standard deviation, skewness, and kurtosis.
Generating Data Using Flexible Families of Distributions
The Pearson and Johnson systems are flexible parametric families of distributions that provide good matches for a wide range of data shapes.