Hi guys.

I am trying to compare 3 pymc models. One doing exponential regression, one with inverted s-shape regression and one with linear regression. The arviz compare gives me the following outcome

```
rank elpd_loo p_loo weight se warning scale
s_regression_model 0 -74.675459 4.038866 0.733810 5.034438 False log
linear_regression_model 1 -75.797628 3.434888 0.057797 5.323788 False log
exp_regression_model 2 -80.965069 5.353204 0.208393 8.190495 False log
```

What i find strange is that the weight of linear model which is second in rank is smaller than the weight of the exponential model which is third in rank. Shouldn’t the weights be “analogous” to the ranks?

But if i compare linear to exponential model (just these two) then indeed the weight of the linear model is bigger than the weight of the exponential model.

```
rank elpd_loo p_loo weight se warning scale
linear_regression_model 0 -75.797628 3.434888 0.784209 5.323788 False log
exp_regression_model 1 -80.965069 5.353204 0.215791 8.190495 False log
```

My question is, if the rank of the model in a 3-model comparison is higher shouldn’t the weight be bigger also? Am I missing something here? Is it ok this outcome?

Thanks a lot in advance.