# Should find\_MAP() be used for gaussian process models?

**URL:** <https://discourse.pymc.io/t/should-find-map-be-used-for-gaussian-process-models/5131>\
**Category:** Questions\
**Created:** [May 21, 2020, 7:28pm UTC](https://discourse.pymc.io/t/should-find-map-be-used-for-gaussian-process-models/5131 "2020-05-21T19:28:29Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![mina](https://avatars.discourse-cdn.com/v4/letter/m/839c29/32.png) [@mina](https://discourse.pymc.io/u/mina)\
**Post date:** [May 21, 2020, 7:28pm UTC](https://discourse.pymc.io/t/should-find-map-be-used-for-gaussian-process-models/5131/1 "2020-05-21T19:28:29Z")

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The [Mauna Loa example](https://docs.pymc.io/notebooks/GP-MaunaLoa.html) uses `find_MAP()`, but I think since that example was written, a warning was added to pymc3 that "`find_MAP` should not be used to initialize the NUTS sampler. Simply call `pymc3.sample()` and it will automatically initialize NUTS in a better way."

Is `find_MAP()` still the recommended way to fit a gaussian process model? Or should I always be using NUTS instead?

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**Author:** ![tirthasheshpatel](https://avatars.discourse-cdn.com/v4/letter/t/ac91a4/32.png) [@tirthasheshpatel](https://discourse.pymc.io/u/tirthasheshpatel)\
**Post date:** [May 22, 2020, 6:01am UTC](https://discourse.pymc.io/t/should-find-map-be-used-for-gaussian-process-models/5131/2 "2020-05-22T06:01:25Z")

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The warning says that you shouldn’t use `find_MAP` to **initialize** the chain. It will automatically initialize it smartly if you are using `pm.sample` with NUTS. But they are two independent inference methods altogether. You can either use `find_MAP` to infer the parameters of the model or use MCMC methods according to the size of your data and your needs.

Coming to your question, Yes, you can use `find_MAP` to fit a GP model. In fact, that’s what most of the papers and practical methods tell you to do.

OTOH, PyMC3 provides nice MCMC methods that can also be used on a GP model. Again, it’s upto you what you choose.

The main difference between these methods is that `find_MAP` may get stuck at a local minima, plateau (flat surfaces) or other non-convex high dimensional optimization problems while NUTS performs very good on high dimensional spaces and provides unbiased estimates of model parameters in a long run (with a downside of being slow on larger datasets).