I knew I was going to do that.
marginal t-distribution reference

From Lysy:
3. Suppose that V ~ iWish(Psi, nu) and
            B | V ~ matNorm( Lambda, V\kron Omega^{-1} ).

To get the marginal distribution of B_{ij}, note that

(B_{i1}, ... B_{iq}) | V ~ N( (Lambda_{i1}, ..., Lambda_{iq}), V / kappa ),

where kappa = 1/ [Omega^{-1}]_ii.  So each row of B is just
Normal-Inverse-Wishart.

The parameters of the marginal t-distribution of B_{ij} are
given in equation (256) of http://www.cs.ubc.ca/~murphyk/Papers/bayesGauss.pdf.
tweak density plots to be readable
Work in a hack that allows plot.densities to take a matrix of functions--in prep for analytic densities
NIW.densities(): analytic marginal p.d.f.s
bugfix
rearrange code via dependency chains
Analytic density plots run finally and fail gracefully; they do not plot correctly, however.
repair analytic densities. I THINK THEY ACTUALLY WORK NOW

also speed them up with reasonable_subset while we're at it
and patch reasonable_subset to support vectors
typo

y'know, it's interesting that the analytic results are notably lamer than the comp. ones
because the comp ones had a pdf for every plot
but the analytic results fail a bunch

Also, bug: the t-distribution's parameters are wrong, like a jerk.