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This is usually needed for Multivariate distributions.
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You can see an example in {class}`~pymc.tests.distributions.test_multivariate.TestDirichlet`.
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You can see an example in {class}`~tests.distributions.test_multivariate.TestDirichlet`.
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### Notes on `check_pymcs_draws_match_reference` test
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@@ -302,17 +302,17 @@ The latter kind of test (if warranted) can be performed with the aid of `pymc_ra
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This kind of test only makes sense if there is a good independent generator reference (i.e., not just the same composition of NumPy / SciPy calls that is done inside `rng_fn`).
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Finally, when your `rng_fn` is doing something more than just calling a NumPy or SciPy method, you will need to set up an equivalent seeded function with which to compare for the exact draws (instead of relying on `seeded_[scipy|numpy]_distribution_builder`).
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You can find an example in {class}`~pymc.tests.distributions.test_continuous.TestWeibull`, whose `rng_fn` returns `beta * np.random.weibull(alpha, size=size)`.
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You can find an example in {class}`~tests.distributions.test_continuous.TestWeibull`, whose `rng_fn` returns `beta * np.random.weibull(alpha, size=size)`.
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## 4. Adding tests for the `logp` / `logcdf` methods
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Tests for the `logp` and `logcdf` mostly make use of the helpers `check_logp`, `check_logcdf`, and
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`check_selfconsistency_discrete_logcdf` implemented in `~pymc.tests.distributions.util`
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`check_selfconsistency_discrete_logcdf` implemented in `~tests.distributions.util`
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