mmm_attribution

mmm_attribution estimates attribution from aggregated marketing signals. The function separates the structural variable mapping from measure-level aggregation weights:

• D_variables maps each raw input variable to a final channel and measure.
• D_measures is optional and can define global aggregation_weight values by measure. If D_measures is not provided, the function uses automatic measure handling.

PARAMETER	TYPE	DEFAULT	DESCRIPTION
Data	data.frame / table	required	Aggregated dataset containing a timestamp column, the target column, and the marketing or business signal columns used for attribution.
D_variables	data.frame / table	required	Mapping table with one row per input signal. It must contain variable, channel, and measure. The target column must not be included.
D_measures	data.frame / table / "auto"	"auto"	Optional measure-level weighting table. The recommended user-facing structure contains columns measure and aggregation_weight. If omitted or set to "auto", measure handling is estimated automatically.
target	string	required	Name of the target column in Data. The target must exist in Data and must not be included in D_variables.
model	string	"linear"	Attribution engine. Allowed values are "linear", "reward", and "copula".
max_p	integer	12	Maximum lag depth considered when evaluating the relationship between input signals and the target.
nsim	integer	1000	Simulation parameter used by model components that require simulation, kept for API consistency.
seed	integer	1234567	Random seed used for reproducible results where random or simulation-based components are involved.
return_diagnostics	bool	False	If True, returns additional diagnostic tables useful to inspect signal weights, scoring, saturation, and attribution shares.
verbose	integer / bool	1	Controls runtime logging. Use 0 or False to reduce printed output.
ncore	integer	1	Number of cores used by supported computation steps.
password	string	optional	ChannelAttributionPro license token.

Example structure for D_variables:

variable	channel	measure
google_clicks	google_ads	clicks
google_impressions	google_ads	impressions
facebook_clicks	facebook_ads	clicks
facebook_impressions	facebook_ads	impressions
direct_searches	direct	direct_searches

Example structure for D_measures:

measure	aggregation_weight
direct_searches	0.45
clicks	0.45
impressions	0.10

aggregation_weight is used when variable-level attributions sharing the same channel are aggregated into final channel-level attribution. The internal signal scaling is estimated automatically from the data.