So I'm using 1Distributions.jl1, and I sample from a multivariant normal - I'd expect a sample for N random variables to be size N, not 1.
Here is my code - am I misinterpreting what this is doing, or is my code just wrong?
using Distributions
using LinearAlgebra
N = 3
mu =[1,1,1]
cov = Matrix(1.0I, N, N)
d = MvNormal(mu,cov)
x =rand(d,100)
println(x[1])
When I look at the first sample, instead of being length 3, it is a scalar:
julia> include("dist.jl")
-0.02020323039551508
The results are returned as a Matrix not a set of tuples:
julia> rand(d,10)
3×10 Matrix{Float64}:
0.99872 1.67639 2.13745 0.961745 … 1.74531 0.831261 0.104456 2.57985
-0.503303 1.54691 1.72998 1.73453 1.02923 0.717212 2.99329 0.181151
0.967349 0.786567 2.02966 1.02071 0.892649 3.63519 -0.374087 -0.347399
x[1] just returned the first element of the matrix.
Hence you can get the first element as (@view is to avoid data copying):
julia> @view x[:,1]
3-element view(::Matrix{Float64}, :, 1) with eltype Float64:
0.7978125656624844
1.6078955127154368
1.376647003099504