Getting Started¶
First we need to include Sigma
julia> using Sigma
Then, we create a uniform distribution x
and draw 100 samples from it using rand
:
julia> x = uniform(0,1)
RandVar{Float64}
julia> rand(x, 100)
100-element Array{Float64,1}:
0.376264
0.492391
...
Then we can find the probability that x^2
is greater than 0.6:
julia> prob(x^2 > 0.6)
[0.225463867187499 0.225463867187499]
Then we can introduce an exponentially distributed variable y
, and find the probability that x^2
is greater than 0.6 under the condition that the sum of x
and y
is less than 1
julia> y = exponential(0.5)
julia> prob(x^2 > 0.6, x + y < 1)
[0.053548951048950494 0.06132144691466614]
Then, instead of computing conditional probabilities, we can sample from x
under the same condition:
julia> rand(x, x + y < 1)
0.04740462764340371