# Random variable is nan: Poisson-gamma model for grouped data

**URL:** <https://discourse.mc-stan.org/t/random-variable-is-nan-poisson-gamma-model-for-grouped-data/2282>\
**Category:** Modeling\
**Created:** [October 23, 2017, 4:14pm UTC](https://discourse.mc-stan.org/t/random-variable-is-nan-poisson-gamma-model-for-grouped-data/2282 "2017-10-23T16:14:58Z")\
**Posts on this page:** 1\
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**Author:** ![bbbales2](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/bbbales2/32/77_2.png) [@bbbales2](https://discourse.mc-stan.org/u/bbbales2)\
**Post date:** [October 23, 2017, 4:40pm UTC](https://discourse.mc-stan.org/t/random-variable-is-nan-poisson-gamma-model-for-grouped-data/2282/2 "2017-10-23T16:40:38Z")

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Variables in Stan are default NaNs unless you set them to anything else, so in the block:

```stan
model {
  matrix[I,J] lambda; // <-- lambda will be NaNs unless you set them equal to something
  ...
}

```

`target +=gamma_lpdf(lambda[i,j]|alpha[j],beta[j]);` or equivalently `lambda[i, j] ~ gamma(alpha[j],beta[j]);` don’t do any assignment to lambda.

Do you mean for lambda to be a parameter that gets sampled? If so, define it in the parameters block.

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