# Non-deterministic MCMC model with updates

**URL:** <https://discourse.pymc.io/t/non-deterministic-mcmc-model-with-updates/2340>\
**Category:** Questions\
**Created:** [December 6, 2018, 2:29pm UTC](https://discourse.pymc.io/t/non-deterministic-mcmc-model-with-updates/2340 "2018-12-06T14:29:17Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![colcarroll](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/colcarroll/32/9_2.png) [@colcarroll](https://discourse.pymc.io/u/colcarroll)\
**Post date:** [December 6, 2018, 6:14pm UTC](https://discourse.pymc.io/t/non-deterministic-mcmc-model-with-updates/2340/2 "2018-12-06T18:14:02Z")

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This looks related to [Predicting out-of-sample for autoregressive models](https://discourse.pymc.io/t/predicting-out-of-sample-for-autoregressive-models/984/5). The short version is that you are writing down a model for `Y` using `X1` and `X2`, so you might use the parameters you learn with PyMC3 to generate samples going forward, or pad `X1` and `X2` with `NaN`'s.

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_[View the full topic](https://discourse.pymc.io/t/non-deterministic-mcmc-model-with-updates/2340)._