causalis.dgp.panel_data_did.functional.PanelOutputPanelOutput
None
Python Docs
causalis
Package entry
causalisRoot package overview and namespace mapNamespaces
causalis.dgp.panel_data_did.functionalSubmodule causalis.dgp.panel_data_did.functional with no child pages and 7 documented members.
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causalis.dgp.panel_data_did.functional.PanelOutputNone
causalis.dgp.panel_data_did.functional.generate_did_dataGenerate a realistic Gaussian DID panel with a common adoption date.
The outcome is a continuous marketplace-style metric generated from unit size, demand seasonality, macro shocks, competition, average order value, serially correlated unit noise, and a post-adoption relative lift for all treated units. Oracle columns expose the untreated counterfactual and true effect on each treated post-treatment row.
causalis.dgp.panel_data_did.functional.generate_did_gamma_dataGenerate a realistic Gamma DID panel for positive continuous outcomes.
Preferred usage is explicit n_pre_periods and n_post_periods. If both
are omitted, they are inferred from n.
causalis.dgp.panel_data_did.functional.generate_did_poisson_dataGenerate a realistic Poisson DID panel for count outcomes.
Preferred usage is explicit n_pre_periods and n_post_periods. If both
are omitted, they are inferred from n.
causalis.dgp.panel_data_did.functional.generate_did_gammaScenario-style Gamma DID wrapper with Causalis 26 naming.
causalis.dgp.panel_data_did.functional.generate_did_gamma_26_dataNone
Canonical target
causalis.dgp.panel_data_did.functional.generate_did_gamma_26_data
causalis.dgp.panel_data_did.functional.generate_did_poisson_26_dataScenario-style Poisson DID wrapper with Causalis 26 naming.
Canonical target
causalis.dgp.panel_data_did.functional.generate_did_poisson_26_data