meridian.model.eda.eda_outcome.PriorQualityData

Container for prior quality check metrics for a single channel.

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__

Return self==value.

bimodal_statistic None