MMMPlotSuite

class pymc_marketing.mmm.plot.MMMPlotSuite(idata)

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 the allocated contribution by channel with uncertainty intervals.
MMMPlotSuite.budget_allocation(samples[, ...])	Plot the budget allocation and channel contributions.
MMMPlotSuite.channel_contribution_share_hdi([...])	Plot the share of channel contributions in a forest plot.
MMMPlotSuite.channel_parameter(param_name[, ...])	Plot the posterior distribution of a channel parameter using violin plots.
MMMPlotSuite.contributions_over_time(var[, ...])	Plot the time-series contributions for each variable in var.
MMMPlotSuite.cv_crps(results[, dims])	Plot CRPS scores for train and test sets across CV splits.
MMMPlotSuite.cv_predictions(results[, dims])	Plot posterior predictive predictions across CV folds.
MMMPlotSuite.marginal_curve([hdi_prob, ax, ...])	Plot precomputed marginal effects stored under idata.sensitivity_analysis['marginal_effects'].
MMMPlotSuite.param_stability(results, parameter)	Plot parameter stability across CV iterations.
MMMPlotSuite.posterior_distribution(var[, ...])	Plot the posterior distribution of a variable across a specified dimension.
MMMPlotSuite.posterior_predictive([var, ...])	Plot time series from the posterior predictive distribution.
MMMPlotSuite.prior_predictive([var, idata, ...])	Plot time series from the posterior predictive distribution.
MMMPlotSuite.prior_vs_posterior(var[, ...])	Plot the prior vs posterior distribution for a variable across a dimension.
MMMPlotSuite.residuals_over_time([hdi_prob])	Plot residuals over time by taking the difference between true values and predicted.
MMMPlotSuite.residuals_posterior_distribution([...])	Plot the posterior distribution of residuals.
MMMPlotSuite.saturation_curves(curve[, ...])	Overlay saturation‑curve scatter‑plots with posterior‑predictive sample curves and HDI bands.
MMMPlotSuite.saturation_curves_scatter([...])	Plot scatter plots of channel contributions vs. channel data.
MMMPlotSuite.saturation_scatterplot([...])	Plot the saturation curves for each channel.
MMMPlotSuite.sensitivity_analysis([...])	Plot sensitivity analysis results.
MMMPlotSuite.uplift_curve([hdi_prob, ax, ...])	Plot precomputed uplift curves stored under idata.sensitivity_analysis['uplift_curve'].
MMMPlotSuite.waterfall_components_decomposition([...])	Create a waterfall plot showing the decomposition of the target into its components.