meridian.model.eda.eda_outcome.PriorQualityData

Container for prior quality check metrics for a single channel.

meridian.model.eda.eda_outcome.PriorQualityData(
    channel_name: str,
    prior_width_ratio: float,
    baseline_prior_type: str,
    overlap_percentage: float,
    n_negative_experiments: int,
    bimodal_statistic: (float | None) = None
)

Attributes
channel_name	Name of the media channel.
prior_width_ratio	Ratio of the prior 80% CI width to the default LogNormal prior width.
baseline_prior_type	String representation of the baseline prior distribution type (e.g. 'LogNormal', 'Normal', 'ImproperUniform').
overlap_percentage	Overlap coefficient between empirical intermediary distribution and fitted parameterized prior (in [0.0, 1.0]).
n_negative_experiments	Number of experiments for this channel with negative point estimates.
bimodal_statistic	Bimodality statistic for the calibrated prior (0.0=unimodal, 1.0=bimodal analytical, Hartigan's Dip Test statistic, or None if not available).

Methods

__eq__

__eq__(
    other
)

Return self==value.

Class Variables
bimodal_statistic	None