Hi Bradley
I was able to construct an GMM instance with
julia> Σnew =
Triangular{Float64,Matrix{Float64},:U,false}[chol(sigma[:,:,i], :U) for i =
1:2]
julia> GMM(p, mu, Σnew, [], 0)
GMM{Float64} with 2 components in 2 dimensions and full covariance
Mix 1: weight 0.900000
mean: 1x2 Array{Float64,2}:
0.0 25.0
covariance: 2x2 Array{Float64,2}:
5.26316 -4.73684
-4.73684 5.26316
Mix 2: weight 0.100000
mean: 1x2 Array{Float64,2}:
0.0 25.0
covariance: 2x2 Array{Float64,2}:
0.133333 0.0
0.0 0.133333
but I don't understant the last two arguments to the constructor.
2014-12-18 1:06 GMT+01:00 Bradley Setzler <[email protected]>:
>
> Hi,
>
> I wish to work with the Gaussian Mixture distribution (especially rand
and pdf), exactly as in this example:
>
> mu = [0.0 25.0; 0.0 25.0]
> sigma = Array(Float64, 2, 2, 2)
> sigma[:, :, 1] = [1.0 0.9; 0.9 1.0]
> sigma[:, :, 2] = 7.5 * [1.0 0.0; 0.0 1.0]
> p = [0.9, 0.1]
>
> distr = MixtureMultivariateNormals(mu, sigma, p)
> X = rand(distr, 10_000)
>
>
> However, the method MixtureMultivariateNormals(mu, sigma, p) used in that
example no longer exists. The maintained version of MixtureModels.jl has no
examples or methods in the documentation of basic usage, and it is far from
obvious how to use it for a Gaussian mixture.
>
> Separately, the package GaussianMixtures.jl, does not successfully work
in what would seem to be the obvious method:
>
> julia> GMM(p,mu,sigma)
> ERROR: `GMM{T<:FloatingPoint,CT<:Union(Array{T,2},Array{T,1})}` has no
method matching
GMM{T<:FloatingPoint,CT<:Union(Array{T,2},Array{T,1})}(::Array{Float64,1},
::Array{Float64,2}, ::Array{Float64,2})
>
> Could someone show me a working example analogous to the one above, using
whichever package you wish?
>
> Thank you,
> Bradley
