diff_diff.MeridianROIPrior#

class diff_diff.MeridianROIPrior[source]#

Bases: object

Lognormal prior parameters for Meridian’s roi_m/mroi_m calibration.

mu/sigma reproduce meridian.model.prior_distribution. lognormal_dist_from_mean_std(roi_mean, roi_sd) exactly (closed form; no Meridian dependency). parameter records which Meridian prior the caller is informing ("roi_m" or "mroi_m"). per_experiment records each pooled experiment’s ROI, widened sd, spend, and spend weight.

Methods

`__init__`(roi_mean, roi_sd, mu, sigma[, ...])
`to_code`(*[, channel, media_channels, ...])	Ready-to-paste Meridian snippet (channel- and time-scoped; 1.7.0 pinned).
`to_dict`()

Attributes

`parameter`
`per_experiment`
`roi_mean`
`roi_sd`
`mu`
`sigma`

__init__(roi_mean, roi_sd, mu, sigma, parameter='roi_m', per_experiment=())#

Parameters:

roi_mean (float)
roi_sd (float)
mu (float)
sigma (float)
parameter (str)
per_experiment (Tuple[ExperimentROI, ...])

Return type:

None

classmethod __new__(*args, **kwargs)#