Omega
As described in [models], random variables are thin wrappers around functions which take as input a value ω::Ω
We previously described Ω
as a type of AbstractRNG
. This is true, but the full store is a bit more complex
Ω
Ω
is an abstract type which represents a sample space in probability theory.
Missing docstring for Ω
. Check Documenter's build log for details.
Missing docstring for SimpleΩ
. Check Documenter's build log for details.
Samplers vs Random Variables
A sampler and a random variable have many similarities but are different. To demonstrate the difference, we shall show the changes one has to make to turn a sampler into an Omega RandVar
.
Create a sampler that
x1() = rand() > 0.5
x1
uses Random.GLOBAL_RNG
in the background. Instead, make it explicit:
julia> x2(rng::AbstractRNG) = rand(rng) > 0.5
julia> x2(Random.MersenneTwister())
false
Make a cosmetic change
julia> x2(rng::AbstractRNG) = rand(rng) > 0.5
julia> x2(Random.MersenneTwister())
false