Hi

Is there a package implementing a block RWMH algorithm?

With block, I mean partitioning the parameter vector. Preferably one where I can choose the partition ex ante, but one with random blocks every draw works as well.

Thanks for any suggestions!

I put this in the Julia Slack, but I’ll repost here for posterity.

You can sort of do this with Gibbs sampling:

```
spl = Gibbs(
MH(:a1, :a2),
MH(:a3, :a4)
)
sample(model, spl, n)
```

if you want static MH (unconditional proposal distributions). If you have a proposal matrix and want to do random-walk MH you should be able to do

```
spl = Gibbs(
MH(Sigma1, :a1, :a2),
MH(Sigma2, :a3, :a4)
)
sample(model, spl, n)
```

for proposal matrices `Sigma1`

and `Sigma2`

.