Build a sampler for your model

aemcmc.basic.construct_sampler(obs_rvs_to_values, srng)

Eagerly construct a sampler for a given set of observed variables and their observations.

Parameters:

obs_rvs_to_values – A dict of variables that maps stochastic elements (e.g. RandomVariables) to symbolic Variables representing their observed values.

Returns:

• A dict that maps each random variable to its sampler step and

• any updates generated by the sampler steps.

The Sampler object

construct_sampler returns a Sampler object that contains the graphs for the variables’ sampling steps and the updates to pass to aesara.function:

class aemcmc.types.Sampler(sample_steps, updates=<factory>, parameters=<factory>)

A class that tracks sampling steps and their parameters.

parameters

Parameters needed by the sampling steps.

sample_steps

A map between measures and their updated value under the current sampling scheme.

stages

A list of the sampling stages sorted in scan order.

updates

Updates to be passed to aesara.function