# Traceplot: ValueError: zero-size array to reduction operation maximum which has no identity

**URL:** <https://discourse.pymc.io/t/traceplot-valueerror-zero-size-array-to-reduction-operation-maximum-which-has-no-identity/310>\
**Category:** Questions\
**Created:** [September 7, 2017, 11:08pm UTC](https://discourse.pymc.io/t/traceplot-valueerror-zero-size-array-to-reduction-operation-maximum-which-has-no-identity/310 "2017-09-07T23:08:59Z")\
**Posts on this page:** 1\
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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:** [September 9, 2017, 7:44am UTC](https://discourse.pymc.io/t/traceplot-valueerror-zero-size-array-to-reduction-operation-maximum-which-has-no-identity/310/10 "2017-09-09T07:44:24Z")

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You model will run into problem quite easily, as the `model_err` is not bounded: if `model_err**2` \> `y_est*(1 - y_est)` the Beta distribution is undefined. You can try doing:

`model_err = pm.Uniform('model_err',lower=0, upper=y_est*(1-y_est), shape=(2481,))`

eg, see linke below about infering a comment rate - with reparameterization using the mean [http://stats.stackexchange.com/questions/67443/does-the-beta-distribution-have-a-conjugate-prior/67700](http://stats.stackexchange.com/questions/67443/does-the-beta-distribution-have-a-conjugate-prior/67700)  
[http://stats.stackexchange.com/questions/12232/calculating-the-parameters-of-a-beta-distribution-using-the-mean-and-variance/12239](http://stats.stackexchange.com/questions/12232/calculating-the-parameters-of-a-beta-distribution-using-the-mean-and-variance/12239)

You can also reparameterized it using the mode, see John K. Kruschke 2015, cf. Eqn 9.4, pp. 223, also pp. 236 Figure 9.7 for the estimation of kappa using a Gamma prior.

Otherwise, try the logit-normal model as @aseyboldt said in [Beta Regression in pyMC3](https://discourse.pymc.io/t/beta-regression-in-pymc3/301/7?u=junpenglao)

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