Sampling from two-dimensional distribution

I have trouble in implement sampling inference for two-dimensional distribution with pymc.
For example, how to implement an inference for two-dimensional normal distribution?
If I have known a tow-dimensional arbitrary two-dimensional distribution function, how can I implement inference?

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Can you provide a bit more detail about what you are trying to do? Or maybe you can provide some code to generate the sort of data you are envisioning?


I have some data, and I want to use these data to infer the parameters in this joint distribution.

Actually I don’t know how to use pymc to infer the parameters from a two-dimensional joint distribution.

So I want to start with a simple case that how to infer the two-dimensional normal distribution using generating data firstly.