update documentation
organize documentation
Naive Normal-Inverse-Wishart sampler
Tidy debugging up and out.
experimenting with the efficient algorithm; there's seems to be an inconsistency here:

U_i does NOT give a lower triangular matrix, which means that we cannot use back-solving.
testing braindump
A place for derivations we will need and perhaps should include in our report.
An analysis of R's rWishart.c, which has no comments explaining how does what it does.
finish the analysis and tidy the pseudocode
gitignore
conventionalize naming
reference papers
more things to prove
derivations? why are my matrices not conforooooororrming
plan.txt
I seem to have found a bug: the way it's phrased, we get V = ULUL or LULU which has no particularly efficient method to compute with..
more proofs
noooooooooo, this line was very wrong. proof-by-computer shows the new one is correct.

This is the proof by computer:
a=20000; b=10; X = rnorm(a*b); dim(X) = c(a,b); S=t(X)%*%X; norm(chol(solve(S)) - solve(chol(S)))
run it enough times and vary a and b and tell me the chance that this theorem is wrong.
notes
Basic timing tests for different Ax=b solvers.