# pm.Multinomial gives Sampling Error

**URL:** <https://discourse.pymc.io/t/pm-multinomial-gives-sampling-error/10639>\
**Category:** v5\
**Tags:** bug\
**Created:** [October 20, 2022, 7:01am UTC](https://discourse.pymc.io/t/pm-multinomial-gives-sampling-error/10639 "2022-10-20T07:01:50Z")\
**Posts on this page:** 1\
**Showing post:** 3

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**Author:** ![ricardoV94](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/ricardov94/32/5775_2.png) [@ricardoV94](https://discourse.pymc.io/u/ricardoV94)\
**Post date:** [October 20, 2022, 8:01am UTC](https://discourse.pymc.io/t/pm-multinomial-gives-sampling-error/10639/3 "2022-10-20T08:01:30Z")

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@gms101 That’s definitely a bug, I opened an issue on the PyMC repository: [Multinomial moment produces invalid values for some parameters · Issue #6233 · pymc-devs/pymc · GitHub](https://github.com/pymc-devs/pymc/issues/6233)

In the meantime you can tell PyMC to use a sample from the prior as the `initval` to avoid the error (or pass a valid numerial initval manually):

```python
import pymc as pm

with pm.Model() as m:
  p = [0.1441,0.1363,0.1385,0.1348,0.1521,0.1500,0.1442]
  x = pm.Multinomial("x", n=[2, 6, 4], p=p, initval="prior")

```

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