simulation

Simulation result containers.

Classes:

Name	Description
`SimulationInferenceState`	Simulation inference results for post-fit or power analysis simulations.

Classes¶

SimulationInferenceState¶

Simulation inference results for post-fit or power analysis simulations.

Created by: build_simulation_inference_state(), compute_simulation_inference() Consumed by: build_simulations_dataframe(), model.simulations Augmented by: Never

Attributes:

Name	Type	Description
`alpha`	`float`
`bias`	`dict[str, float]`
`coverage`	`dict[str, float]`
`n_sims`	`int`
`power`	`dict[str, float]`
`rmse`	`dict[str, float]`
`sim_mean`	`ndarray \| None`
`sim_quantiles`	`dict[str, ndarray]`
`sim_sd`	`ndarray \| None`
`sim_type`	`str`
`true_coef`	`dict[str, float]`

Attributes¶

alpha¶

alpha: float = field(default=0.05, validator=[validators.instance_of((int, float)), validators.gt(0), validators.lt(1)])

bias¶

bias: dict[str, float] = field(factory=dict, validator=(validators.instance_of(dict)))

coverage¶

coverage: dict[str, float] = field(factory=dict, validator=(validators.instance_of(dict)))

n_sims¶

n_sims: int = field(validator=is_positive_int)

power¶

power: dict[str, float] = field(factory=dict, validator=(validators.instance_of(dict)))

rmse¶

rmse: dict[str, float] = field(factory=dict, validator=(validators.instance_of(dict)))

sim_mean¶

sim_mean: np.ndarray | None = field(default=None, validator=is_optional_ndarray)

sim_quantiles¶

sim_quantiles: dict[str, np.ndarray] = field(factory=dict, validator=(validators.instance_of(dict)))

sim_sd¶

sim_sd: np.ndarray | None = field(default=None, validator=is_optional_ndarray)

sim_type¶

sim_type: str = field(validator=(validators.in_(('post_fit', 'power_analysis'))))

true_coef¶

true_coef: dict[str, float] = field(factory=dict, validator=(validators.instance_of(dict)))