MHKernel

class liesel.goose.MHKernel(position_keys, proposal_fn, initial_step_size=1.0, da_tune_step_size=False, da_target_accept=0.234, da_gamma=0.05, da_kappa=0.75, da_t0=10)

Bases: ModelMixin, TransitionMixin[RWKernelState, DefaultTransitionInfo]

A Metropolis-Hastings kernel implementing the Kernel protocol.

The user needs to provide a proposal function that proposes a new state and the log_correction.

If da_tune_step_size is True the stepsize passed as an argument to the proposal function is tuned using the dual averging algorithm. Step size is tuned on the fly during all adaptive epochs.

Methods

end_epoch(prng_key, kernel_state, ...)	Sets the step size as found by the dual averaging algorithm.
end_warmup(prng_key, kernel_state, ...)	Currently does nothing.
has_model()	Whether the model interface is set.
init_state(prng_key, model_state)	Initializes the kernel state.
log_prob_fn(model_state)	Returns the log-probability function with the position as the only argument.
position(model_state)	Extracts the position from a model state.
set_model(model)	Sets the model interface.
start_epoch(prng_key, kernel_state, ...)	Resets the state of the dual averaging algorithm.
transition(prng_key, kernel_state, ...)	Handles one transition.
tune(prng_key, kernel_state, model_state, epoch)	Currently does nothing.

Attributes

error_book	Dict of error codes and their meaning.
identifier	Kernel identifier, set by EngineBuilder
model	Returns the model interface if it is set.
needs_history	Whether this kernel needs its history for tuning.
position_keys	Tuple of position keys handled by this kernel.