How to generate random values from a distribution (in Julia)

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Task

There are many famous continuous probability distributions, such as the normal and exponential distributions. How can we get access to them in software, to generate random values from a chosen distribution?

Related tasks:

• How to compute probabilities from a distribution
• How to plot continuous probability distributions
• How to plot discrete probability distributions

Solution

You can import many different random variables from Julia’s Distributions package. The full list of them is online here.

If you don’t have that package installed, first run using Pkg and then Pkg.add( "Distributions" ) from within Julia.

Regardless of whether the distribution is discrete or continuous, the appropriate function to call is rand. Here are two examples.

Using a normal distribution:

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using Distributions
X = Normal( 5, 3 )
rand( X, 10 )

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10-element Vector{Float64}:
 2.18036354985213
 4.261755639220276
 9.175724974437623
 7.111178500969482
 5.784059237346303
 2.276916458848387
 4.323059921916803
 7.067942300207913
 5.040815993440384
 5.401080085074974

Using a uniform distribution:

In this example, we generate the random values in one line of code, without giving the random variable a name.

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using Distributions
rand( Uniform( 100, 200 ), 5 )

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5-element Vector{Float64}:
 120.34366617283129
 117.18012200542422
 121.03058480958376
 140.31797801233535
 109.153400454394

Content last modified on 24 July 2023.

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Contributed by Nathan Carter (ncarter@bentley.edu)