# Creating a Custom Hypersecant distribution

**URL:** <https://discourse.pymc.io/t/creating-a-custom-hypersecant-distribution/10255>\
**Category:** v3\
**Created:** [August 29, 2022, 1:23pm UTC](https://discourse.pymc.io/t/creating-a-custom-hypersecant-distribution/10255 "2022-08-29T13:23:35Z")\
**Posts on this page:** 1\
**Showing post:** 6

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**Author:** ![Mojo\_ild](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mojo_ild/32/4703_2.png) [@Mojo\_ild](https://discourse.pymc.io/u/Mojo_ild)\
**Post date:** [October 7, 2022, 6:06pm UTC](https://discourse.pymc.io/t/creating-a-custom-hypersecant-distribution/10255/6 "2022-10-07T18:06:29Z")

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Thank you very much for the reply.

To understand further about the custom distribution class configuration:

- What are the necessary components needed to design the class custom distribution?
- Is it necessary to include the `def random` in the custom distribution?
- What is the reason for getting different fused distributions when implementing the bayesian fusion part? Could it be because of `def random` code section in the custom distribution? For clarification about the fusion part, please find the following question: [How to create Bayesian data fusion in python with pymc3?](https://discourse.pymc.io/t/how-to-create-bayesian-data-fusion-in-python-with-pymc3/10558).

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