# Help with Mixture of Weibull Distribution

**URL:** <https://discourse.pymc.io/t/help-with-mixture-of-weibull-distribution/1079>\
**Category:** Questions\
**Created:** [April 11, 2018, 2:23pm UTC](https://discourse.pymc.io/t/help-with-mixture-of-weibull-distribution/1079 "2018-04-11T14:23:27Z")\
**Posts on this page:** 1\
**Showing post:** 5

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**Author:** ![junpenglao](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/junpenglao/32/8_2.png) [@junpenglao](https://discourse.pymc.io/u/junpenglao)\
**Post date:** [April 12, 2018, 8:09am UTC](https://discourse.pymc.io/t/help-with-mixture-of-weibull-distribution/1079/5 "2018-04-12T08:09:57Z")

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That usually is an indication of bad prior causing your model either unidentifiable or difficult to inference ([Model diagnostics for “Mass matrix contains zeros on the diagonal”](https://discourse.pymc.io/t/model-diagnostics-for-mass-matrix-contains-zeros-on-the-diagonal/957/3)).  
Try changing replacing the uniform prior (usually a bad choice for NUTS) to something more informative, eg  
`shape1 = pm.HalfNormal('shape1', 1.)`

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