matflow.subset_simulation.subset_simulation.generate_next_level_samples_ACS#
- matflow.subset_simulation.subset_simulation.generate_next_level_samples_ACS(performance, num_chains, num_states, dimension, chain_seeds, chain_g, level_idx, master_seed, threshold, chains_per_update, transformation=None, prop_std=1.0, lambda_=1.0, debug=False)#
Generate one conditional level using adaptive conditional sampling (aka adaptive subset infinity).
- Parameters:
chains_per_update – The number of Markov chains (as a fraction of the number of samples per level) that will run before lambda_ is updated. As an integer number, known as Na elsewhere.
prop_std – Initial variance of the proposal distribution.
lambda – Initial scaling parameter.
transformation (Callable | None) –
debug (bool) –
- Return type: