DoubleML 0.3.0

• Use active bindings in the R6 OOP implementation #106 & #93
• Fix the aggregation formula for standard errors from repeated cross-fitting #94 & #95
• Always use the same bootstrap algorithm independent of dml1 vs dml2 and consistent with docu and paper #98 & #99
• Initialize predictions with NA and make sure that there are no missleading entries in the evaluated score functions #96 & #105
• Avoid overriding learner parameters during turing #83 & #84
• Fixes in the exception handling and extension of the unit tests for the score function choice #82
• Prevent overwriting parameters from initialization when calling set_ml_nuisance_params #87 & #89
• Major refactoring and cleanup and extension of the unit test framework #101
• Extension and reorganization of exception handling for DoubleMLData objects #63 & #90
• Introduce style guide and clean up code #80 & #81
• Adaption to be compatible with an API change in the next mlr3 release #103
• Run unit tests with mlr3 in dev version on github actions #104
• Updated the citation info #78, #79 & #86
• Added a short version of and a reference to the arXiv paper as vignette #110 & #113
• Prevent using the subclassed methods check_score and check_data when constructing DoubleML objects #107
• Other refactoring and minor adaptions #91, #92, #102 & #108

DoubleML 0.2.1

• Provide an option to store & export the first-stage predictions #74
• Reduce and refine messaging to the console during estimation #72
• Fix bug in IIVM model if the IV variable is not named z #75
• Fix failing unit test #71
• Added the package logo to the doc

DoubleML 0.2.0

• In the PLR one can now also specify classifiers for ml_m in case of a binary treatment variable with values 0 and 1
• Major refactoring of core-parts of the estimation and tuning of the ML estimators for the nuisance functions: All models now use central helper functions dml_cv_predict() and dml_tune()
• Extensions to the unit test framework to improve upon test coverage
• Added unit test coverage via codecov: https://app.codecov.io/gh/DoubleML/doubleml-for-r
• Minor docu updates and adaptions: #58, #61 & #70

DoubleML 0.1.2

• Adapt calls to mlr3tuning due to a change in their API (since version 0.6.0): fixes #51
• Add bbotk to suggests: fixes R CMD check note #47
• Use doi{} command: fixes R CMD check note #54
• Minor docu updates as DoubleML is now available on CRAN

DoubleML 0.1.1

• First release to CRAN https://cran.r-project.org/package=DoubleML
• Clean up of imports
• Continuous integration was extended by unit tests on github actions https://github.com/DoubleML/doubleml-for-r/actions

DoubleML 0.1.0

• Initial release
• Development at https://github.com/DoubleML/doubleml-for-r
• The R package DoubleML provides an implementation of the double / debiased machine learning framework of Chernozhukov et al. (2018)).
• Implements double machine learning for four different models:
  • Partially linear regression models (PLR) in class DoubleMLPLR
  • Partially linear IV regression models (PLIV) in class DoubleMLPLIV
  • Interactive regression models (IRM) in class DoubleMLIRM
  • Interactive IV regression models (IIVM) in class DoubleMLIIVM
• All model classes are inherited from DoubleML where the key elements of double machine learning are implemented.

DoubleML 0.0.3

create another test pre-release to test the github actions integrations

DoubleML 0.0.2

Merge branch 'master' of github.com:DoubleML/doubleml-for-r into 0.0.X

DoubleML 0.0.1

Merge branch 'master' of github.com:DoubleML/doubleml-for-r into 0.0.X