MMMPlotSuite#

class pymc_marketing.mmm.plot.MMMPlotSuite(idata)[source]#

Media Mix Model Plot Suite.

Provides methods for visualizing the posterior predictive distribution, contributions over time, and saturation curves for a Media Mix Model.

Methods

`MMMPlotSuite.__init__`(idata)
`MMMPlotSuite.allocated_contribution_by_channel_over_time`(samples)	Plot channel contributions over time from budget allocation optimization.
`MMMPlotSuite.budget_allocation`(args, *kwargs)	Create bar chart comparing allocated spend and channel contributions.
`MMMPlotSuite.budget_allocation_roas`(samples)	Plot ROI (Return on Ad Spend) distributions for budget allocation scenarios.
`MMMPlotSuite.contributions_over_time`(var[, ...])	Plot time-series contributions for specified variables.
`MMMPlotSuite.marginal_curve`([data, ...])	Plot marginal effects showing absolute rate of change.
`MMMPlotSuite.posterior_predictive`([var, ...])	Plot posterior predictive distributions over time.
`MMMPlotSuite.saturation_curves`(curve[, ...])	Overlay saturation scatter plots with posterior predictive curves and HDI bands.
`MMMPlotSuite.saturation_scatterplot`([...])	Plot saturation scatter plot showing channel spend vs contributions.
`MMMPlotSuite.sensitivity_analysis`([data, ...])	Plot sensitivity analysis results showing response to input changes.
`MMMPlotSuite.uplift_curve`([data, hdi_prob, ...])	Plot uplift curves showing percentage change relative to baseline.