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ddml 0.9.0

  • Adds ddml_attgt() for staggered DiD and ddml_apo() for average potential outcomes.
  • Adds ddml_policy() for multi-action policy value estimation.
  • Adds ddml() constructor for custom DML estimators with user-supplied scores.
  • Adds lincom() for inference on linear combinations. Supports computation of dynamic average treatment effects via lincom_weights_did().
  • Influence-function-based inference via the ral class; all estimators now inherit from ral.
  • Adds ddml_rep() and ddml_replicate() for repeated cross-fitting with median, mean, or spectral-norm aggregation.
  • Adds diagnostics() for MSPE, R-squared, stacking weights, and CVC tests.
  • Adds fitted/splits pass-through to all ddml_*() estimators.
  • New S3 methods: plot(), as.list(), hatvalues(), nobs(), multi-ensemble tidy()/glance().
  • Adds uniform confidence bands via multiplier bootstrap (confint(uniform = TRUE)).
  • Adds HC0/HC3 variance estimators, parallel computation, stratified cross-fitting, cluster-aware splitting, and input validation.
  • Adds broom compatibility.
  • Fixes ddml_fpliv() with custom weights.
  • Breaking changes:
    • Inference internals use $inf_func instead of $scores/$J/$psi_a/$psi_b.
    • Utility functions (crosspred, crossval, ensemble, ensemble_weights, shortstacking) no longer accept Z/newZ. Pre-concatenate instruments with covariates (e.g., cbind(X, Z)).
    • crosspred() and shortstacking() drop compute_insample_predictions and insample_fitted output.
    • ddml_fpliv() drops the enforce_LIE argument.
    • shortstacking() drops shortstack_y.
    • ddml_*() estimators drop subsamples, cv_subsamples, subsamples_byD, cv_subsamples_byD. Use the new splits parameter instead.

ddml 0.3.0

CRAN release: 2024-10-02

  • Implements one-way clustered inference.
  • Increases defaults for sample_folds and cv_folds to 10.
  • Fixes typo in auxiliary_X arguments.

ddml 0.2.2

CRAN release: 2024-06-26

ddml 0.2.1

CRAN release: 2024-05-26

ddml 0.2.0

CRAN release: 2024-01-09

  • Adds support for the average treatment effect on the treated estimator.
  • Adds support for local average treatment effect estimation with perfect compliance or perfect non-compliance.
  • Adds support for custom ensemble weights.
  • Adds article on integration with the did package.
  • Adds ddml::mdl_glm wrapper for stats::glm().

ddml 0.1.0

CRAN release: 2023-08-29

  • Initial CRAN submission.