Fix bug in SineBivariateVonMises sampler #1628
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fehiepsi
reviewed
Aug 17, 2023
numpyro/distributions/directional.py
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| @@ -477,7 +477,7 @@ def update_fn(curr): | |||
| phi_key, key = random.split(key) | |||
| accept_key, acg_key, phi_key = random.split(phi_key, 3) | |||
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| x = jnp.sqrt(1 + 2 * eig / b0) * random.normal(acg_key, shape) | |||
| x = 1./jnp.sqrt(1 + 2 * eig / b0) * random.normal(acg_key, shape) | |||
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nit: you can use jnp.rsqrt for this.
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Cool, I made the edit.
OlaRonning
approved these changes
Aug 17, 2023
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Thanks @deoxyribose. This is indeed correct and consistent with the R implementation. Could you make a PR with the exact change here aswell.
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See https://cran.r-project.org/web/packages/simdd/index.html for R implementation.
Before fix, highly correlated distributions would fail to sample correctly, and max_sample_iter would exceed the default 1000, silently.
After fix, the same distribution sample correctly distributed values.