Explores generation of samples from a single variable probability distribution.


Updated 17 Jan 2023

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Monte Carlo methods use random sampling to simulate processes of a probabilistic nature and to solve numerical problems approximately. An example application might be the simulation of fluctuations in the positions of detected photons suffering diffraction. These methods rely heavily upon pseudo-random numbers generated by nonlinear computer algorithms and distributed uniformly or normally over a range.
This script explores the generation of samples of a random variable described by an arbitrary probability density function (pdf) and may interest students and teachers of physics and engineering. 'Try this' suggestions are included.

Cite As

Duncan Carlsmith (2023). SampleArbitraryProbabilityDistributionExplorer (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2022b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Added related project.