generate_cuped_tweedie_26
Gold standard Tweedie-like DGP with mixed marginals and structured HTE. Features many zeros and a heavy right tail. Includes two pre-period covariates by default: 'y_pre' and 'y_pre_2'. Wrapper for make_tweedie().
Parameters
- n (
int) – Number of samples to generate. - seed (
int) – Random seed. - add_pre (
bool) – Whether to add pre-period covariates. - pre_name (
str) – Name of the first pre-period covariate column. - pre_name_2 (
str) – Name of the second pre-period covariate column. Defaults tof"{pre_name}_2". - pre_target_corr (
float) – Target correlation between the first pre covariate and post-outcome y in control group. - pre_target_corr_2 (
float) – Target correlation for the second pre covariate. Defaults to a moderate value based onpre_target_corrto reduce collinearity. - pre_spec (
PreCorrSpec) – Detailed specification for pre-period calibration (transform, method, etc.). - include_oracle (
bool) – Whether to include oracle ground-truth columns like 'cate', 'propensity', etc. - return_causal_data (
bool) – Whether to return a CausalData object. - theta_log (
float) – The log-uplift theta parameter for the treatment effect.
Returns
DataFrame or CausalData–