[apathy]

That makes sense, at least as long as the vector- or matrix-valued objective behaves somewhat. I guess I've been using this all along (with transformations to enforce proper behavior) for matrix and tensor completion anyways... Hmm. I just didn't implement it terribly elegantly!

Now that I think about it, all of the methods I've ever seen for matrix-valued time series fits (i.e. multiple measurements at multiple sites per time point) are Bayesian. That's about the most irreducible constrained optimization problem I can think of in this setting.

[mccourt]

Do you have a reference for fitting matrix-valued time series with nonlinear criteria? I'm familiar with the standard Box-Jenkins methods but I usually see that done with linear least-squares methods. I'd love to up my game on that front.

[apathy]

I'm buried under manuscripts right now but making a mental note to look up Mike West's notes when I get home.