gwkokab.inference.poissonlikelihood_utils
=========================================

.. py:module:: gwkokab.inference.poissonlikelihood_utils


Functions
---------

.. autoapisummary::

   gwkokab.inference.poissonlikelihood_utils.analytical_poisson_likelihood_fn
   gwkokab.inference.poissonlikelihood_utils.discrete_poisson_likelihood_fn


Module Contents
---------------

.. py:function:: analytical_poisson_likelihood_fn(model_instance: numpyro.distributions.distribution.Distribution, poisson_mean_estimator: collections.abc.Callable[Ellipsis, tuple[jaxtyping.Array, jaxtyping.Array]], samples_stack: jaxtyping.Array, ln_offsets: jaxtyping.Array, pmean_kwargs: Dict[str, Any], variance_cut_threshold: float | None) -> jaxtyping.Array

.. py:function:: discrete_poisson_likelihood_fn(model_instance: numpyro.distributions.distribution.Distribution, poisson_mean_estimator: collections.abc.Callable[Ellipsis, Tuple[jaxtyping.Array, jaxtyping.Array]], data_group: Tuple[jaxtyping.Array, Ellipsis], log_ref_priors_group: Tuple[jaxtyping.Array, Ellipsis], masks_group: Tuple[jaxtyping.Array, Ellipsis], pmean_kwargs: Dict[str, Any], N_pes: Tuple[jaxtyping.Array, Ellipsis], variance_cut_threshold: float | None) -> jaxtyping.Array