ParetoNBDModel.distribution_new_customer_recency_frequency#

ParetoNBDModel.distribution_new_customer_recency_frequency(data=None, *, T=None, random_seed=None)[source]#

Pareto/NBD process representing purchases across the customer population.

This is the distribution of purchase frequencies given ‘T’ observation periods for each customer.

Parameters:

data (pd.DataFrame, optional) –
DataFrame containing the following columns:
- customer_id: unique customer identifier
- T: time between the first purchase and the end of the observation period.
- covariates: Purchase and dropout covariate columns if original model had any.
If not provided, the method will use the fit dataset.
T (array_like, optional) – Number of observation periods for each customer. If not provided, T values from fit dataset will be used. Not needed if data parameter is provided with a T column.
random_seed (RandomState, optional) – Random state to use for sampling.

Returns:

Dataset containing the posterior samples for the customer population.

Return type:

xr.Dataset