Releases: DoubleML/doubleml-for-r
Releases Β· DoubleML/doubleml-for-r
DoubleML 1.0.0
- Update citation info to publication in Journal of Statistical Software, rename helper function and fix links and GH actions #191
DoubleML 0.5.3
DoubleML 0.5.3
- Add documentation for estimated models for nuisance parameters #181
- New contributor @SvenKlaassen
- Maintenance #179
DoubleML 0.5.2
DoubleML 0.5.1
DoubleML 0.5.0
- Implement a new score function
score = 'IV-type'
for the PLIV model (for details see #161)
--> API change fromDoubleMLPLIV$new(obj_dml_data, ml_g, ml_m, ml_r [, ...])
toDoubleMLPLIV$new(obj_dml_data, ml_g, ml_m, ml_r, ml_g [, ...])
- Adapt the nuisance estimation for the
'IV-type'
score for the PLR model (for details see #161)
--> API change fromDoubleMLPLR$new(obj_dml_data, ml_g, ml_m [, ...])
toDoubleMLPLR$new(obj_dml_data, ml_l, ml_m, ml_g [, ...])
- Use
task_type
instead oflearner_class
to identify whether a learner is meant to regress or classify (this change makes it possible to easily integrate pipelines frommlr3pipelines
as learner for the nuisance functions) #141 - Add Contribution Guidelines, issue templates, a pull request template and a discussion forum to the R package repository #142 #146 #147
- Allow the usage of classifiers for binary outcome variables in the model classes IRM and IIVM #114
- Bug fixes and maintenance #155 #156 #157 #158 #160 #163
DoubleML 0.4.1
DoubleML 0.4.0
- Release highlight: Clustered standard errors for double machine learning models #119
- Apply styler as described in the wiki (https://github.com/DoubleML/doubleml-for-r/wiki/Style-Guidelines) and add a corresponding CI on github actions #120 #122
- Other refactoring, bug fixes and documentation updates #127 #129 #130 #131 #132 #133
DoubleML 0.3.1
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
vsdml2
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