Open ElOceanografo opened 4 years ago
Sorry for the late reply. I am not familiar with these methods, so an example would help clarify.
I actually went and turned my working example into its own small package: https://github.com/ElOceanografo/FactorLoadingMatrices.jl. There's an example in the readme that illustrates the intended usage. Basically the transformation constructs the first m
columns of a Cholesky lower triangle, so you can do dimensionality reduction inside a probabilistic model.
Still happy to contribute the transformation here as well if you want!
Would there be any interest in a "special array" transformation to create loading matrices for factor analysis? i.e., when
n
observed variables are represented bym <= n
latent factors, the loading matrixL
has size(n, m)
and links the latent variablesx
to observed variablesy
asy ~ MvNormal(L * x, sigma)
. When fitting it by MLE/MCMC, all entries above the diagonal are set to zero to ensure the columns are linearly independent. The transform is thus from a vector with(n - m + 2) * m
elements to ann * m
matrix.I've got a working example hacked together that I could turn into a pull request if this would be useful for others...