# Case study on spatial models for areal data - Poisson CAR/IAR

**URL:** <https://discourse.mc-stan.org/t/case-study-on-spatial-models-for-areal-data-poisson-car-iar/481>\
**Category:** Modeling\
**Created:** [May 9, 2017, 8:45pm UTC](https://discourse.mc-stan.org/t/case-study-on-spatial-models-for-areal-data-poisson-car-iar/481 "2017-05-09T20:45:03Z")\
**Posts on this page:** 1\
**Showing post:** 73

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**Author:** ![anon75146577](https://avatars.discourse-cdn.com/v4/letter/a/f07891/32.png) [@anon75146577](https://discourse.mc-stan.org/u/anon75146577)\
**Post date:** [August 16, 2017, 1:09am UTC](https://discourse.mc-stan.org/t/case-study-on-spatial-models-for-areal-data-poisson-car-iar/481/73 "2017-08-16T01:09:15Z")

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That’s a warning about the way HMC worked. It said that in 25 proposals  
the MCMC scheme detected that there could be something wrong.

Now, this is not something to panic about immediately - the diagnostic  
throws out a lot of false positives. There is a lot of infromation in this  
case study.  
[http://mc-stan.org/users/documentation/case-studies/divergences\_and\_bias.html](http://mc-stan.org/users/documentation/case-studies/divergences_and_bias.html)

The take away message is that if thse warnings seem to be concentrating in  
a particular part of the parameter space, then there may be some problems.  
Otherwise they’re probably false positives.

Hope this helps!

D

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