dcegm.pre_processing.model_structure.stochastic_states

Functions

create_stochastic_transition_function(...)	Create the stochastic process transition function.
process_stochastic_transitions(...)	Process stochastic functions.
get_stochastic_transition_vec(transition_funcs, ...)	Return Kron product of stochastic transition functions.
return_dummy_stochastic_transition(*args, **kwargs)
create_stochastic_state_mapping(...)
process_stochastic_model_specifications(model_config)
create_sparse_stochastic_trans_map(model_structure, ...)	Create sparse mapping from state-choice to stochastic states.

Module Contents

dcegm.pre_processing.model_structure.stochastic_states.create_stochastic_transition_function(stochastic_states_transitions, model_config, model_specs, continuous_state_name)

Create the stochastic process transition function.

The output function takes a state-choice vector, params and model_specs as input. It creates a transition vector over cartesian product of exogenous states.

dcegm.pre_processing.model_structure.stochastic_states.process_stochastic_transitions(stochastic_states_transitions, model_config, model_specs, continuous_state_name)

Process stochastic functions.

Parameters:

options (dict) – Options dictionary.

dcegm.pre_processing.model_structure.stochastic_states.get_stochastic_transition_vec(transition_funcs, params, **state_choice_vars)

Return Kron product of stochastic transition functions.

dcegm.pre_processing.model_structure.stochastic_states.return_dummy_stochastic_transition(*args, **kwargs)

dcegm.pre_processing.model_structure.stochastic_states.create_stochastic_state_mapping(stochastic_state_space, stochastic_state_names)

dcegm.pre_processing.model_structure.stochastic_states.process_stochastic_model_specifications(model_config)

dcegm.pre_processing.model_structure.stochastic_states.create_sparse_stochastic_trans_map(model_structure, model_funcs, model_config_processed, from_saved=False)

Create sparse mapping from state-choice to stochastic states.