# Spatial model selection with loo

**URL:** <https://discourse.mc-stan.org/t/spatial-model-selection-with-loo/28051>\
**Category:** brms\
**Tags:** loo\
**Created:** [July 2, 2022, 8:41pm UTC](https://discourse.mc-stan.org/t/spatial-model-selection-with-loo/28051 "2022-07-02T20:41:44Z")\
**Posts on this page:** 1\
**Showing post:** 3

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**Author:** ![cmcd](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/cmcd/32/8601_2.png) [@cmcd](https://discourse.mc-stan.org/u/cmcd)\
**Post date:** [July 4, 2022, 8:50pm UTC](https://discourse.mc-stan.org/t/spatial-model-selection-with-loo/28051/3 "2022-07-04T20:50:45Z")

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Hey @manjago,

In my experience with spatial models, those warning from `loo` are completely typical. I don’t think I’ve ever fit a spatial model that did not result in those `loo` warnings (though I stopped checking a long time ago). Personally, I take it to mean that WAIC (and similar) might be used only as a rough indicator for spatial model comparison.

The discussion that @Carlos_Zarzar linked to is useful, I’ll just point out especially this comment from @betanalpha

> [@WAIC unreliable?](https://discourse.mc-stan.org/t/waic-unreliable/645/5):
>
> Keep in mind that PSIS-LOO, WAIC, DIC, AIC, etc are all approximations to a fundamentally-uncalculatable number that exactly quantifies predictive accuracy. And each of those approximations require different assumptions to be reasonably accurate. A common assumption that’s necessary is that the data are roughly IID so that, for example, looking at a subset of the data gives a reasonable quantification of what a draw from the full data would do. In many models, however, such as the one that Be…

That suggests that these approximations are not well suited for spatial models: we use spatial models both because nearby observations are not IID (there is usually expected similarity), and because a draw from one side of the map is not expected to look like a draw from somewhere else.

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