sccic 0.1.1

New features

• cic() gains a discrete argument (default FALSE). When discrete = TRUE, the discrete CIC estimator of Theorem 4.1 of Athey and Imbens (2006) is used instead of the continuous estimator (Theorem 3.1). The discrete variant correctly handles outcomes with mass points (e.g., integer-valued durations) by integrating the counterfactual over the corresponding quantile band rather than applying a point mapping. Analytic standard errors are suppressed with an informative message when discrete = TRUE, as Theorem 5.1 assumes a continuous distribution; bootstrap inference is recommended instead.

• print.cic() now displays which estimator was used (continuous (Theorem 3.1) or discrete (Theorem 4.1)).

Internal

• Added internal helper functions ecdf_eval_left(), integral_quantile(), and compute_cic_cf() to support the discrete CIC estimator.

sccic 0.1.0

• Initial CRAN release.