Hello,

I am attempting to add in some form of model comparison, weights etc toa project that makes use of cmdstanr.

I have used some of these tools before on brms objects, but never in a project in which I’ve written my own stan code.

Are there any good tutorials that cover current best practices? [There seems to be a range of different packages and approaches]

I am under the impression that the first thing i need to do is to make sure I compute `log_lik[]`

in the `generated quantities {}`

block.

This appears to be working. If I fit my model `m`

I can call m$loo() and I obtain this:

```
Computed from 4000 by 500 log-likelihood matrix
Estimate SE
elpd_loo -375.2 16.6
p_loo 3.1 0.3
looic 750.4 33.2
------
Monte Carlo SE of elpd_loo is 0.0.
All Pareto k estimates are good (k < 0.5).
See help('pareto-k-diagnostic') for details.
```

I have now fitted a second version of my model, `m2`

(which is identical, … I’m just trying to test my code!). Reassuringly, this gives very similar output.

How would I go about computing model weights for these two models?

[Once I have a better handle on what I’m doing, I want to eventually compare my non-linear multi-level model with a linear multi-level model. But, baby steps…]

Thanks