grassp.tl.MgsaResult#

class MgsaResult(sets_results, alpha_post, beta_post, p_post, map_estimate=<factory>, diagnostics=<factory>)[source]#

Container for MGSA posterior summaries and diagnostics.

Parameters:

sets_results#: Per-set report indexed by set name with columns inPopulation, inStudySet, estimate (posterior activity probability, mean over restarts) and std_error (standard deviation over restarts).

alpha_post, beta_post, p_post: Posterior over each parameter grid with columns value, estimate and std_error.

map_estimate#: The maximum-a-posteriori configuration: {"sets": [names], "alpha": float, "beta": float, "p": float, "log_score": float}.

diagnostics#: Sampler settings and MCMC diagnostics (acceptance rates, sample counts, seeds, population/study sizes, per-restart marginals, numba flag).

__init__(sets_results, alpha_post, beta_post, p_post, map_estimate=<factory>, diagnostics=<factory>)#

Parameters:

Return type:

None

Methods

__init__(sets_results, alpha_post, ...[, ...])

Attributes

grassp.tl.MgsaResult