Package: DeepLearningCausal 0.0.104

Nguyen K. Huynh

DeepLearningCausal: Causal Inference with Super Learner and Deep Neural Networks

Functions to estimate Conditional Average Treatment Effects (CATE) and Population Average Treatment Effects on the Treated (PATT) from experimental or observational data using the Super Learner (SL) ensemble method and Deep neural networks. The package first provides functions to implement meta-learners such as the Single-learner (S-learner) and Two-learner (T-learner) described in Künzel et al. (2019) <doi:10.1073/pnas.1804597116> for estimating the CATE. The S- and T-learner are each estimated using the SL ensemble method and deep neural networks. It then provides functions to implement the Ottoboni and Poulos (2020) <doi:10.1515/jci-2018-0035> PATT-C estimator to obtain the PATT from experimental data with noncompliance by using the SL ensemble method and deep neural networks.

Authors:Nguyen K. Huynh [aut, cre], Bumba Mukherjee [aut], Irvin Lee [aut]

DeepLearningCausal_0.0.104.tar.gz
DeepLearningCausal_0.0.104.zip(r-4.5)DeepLearningCausal_0.0.104.zip(r-4.4)DeepLearningCausal_0.0.104.zip(r-4.3)
DeepLearningCausal_0.0.104.tgz(r-4.4-any)DeepLearningCausal_0.0.104.tgz(r-4.3-any)
DeepLearningCausal_0.0.104.tar.gz(r-4.5-noble)DeepLearningCausal_0.0.104.tar.gz(r-4.4-noble)
DeepLearningCausal_0.0.104.tgz(r-4.4-emscripten)DeepLearningCausal_0.0.104.tgz(r-4.3-emscripten)
DeepLearningCausal.pdf |DeepLearningCausal.html✨
DeepLearningCausal/json (API)

Peer review:

Bug tracker:https://github.com/hknd23/deeplearningcausal/issues

On CRAN:

causal-inferencedeep-neural-networksmachine-learning

12 exports 1 stars 1.97 score 146 dependencies 5 scripts 229 downloads

Last updated 1 months agofrom:38595976a3. Checks:OK: 1 NOTE: 6. Indexed: yes.

Exports:complier_modcomplier_predictmetalearner_deepneuralmetalearner_ensembleneuralnet_complier_modneuralnet_pattc_counterfactualsneuralnet_predictneuralnet_response_modelpattc_counterfactualspattc_deepneuralpattc_ensembleresponse_model

Dependencies:backportsbase64encbitbit64bitopsbootbroombslibcachemcaretcaToolscheckmateclassclicliprclockclustercodetoolscolorspacecpp11crayoncvAUCdata.tableDerivdiagramdigestdplyre1071evaluatefansifarverfastmapfontawesomeforcatsforeachforeignFormulafsfuturefuture.applygamgbmgdatagenericsggplot2glmnetglobalsgluegowergplotsgridExtragtablegtoolshardhathavenhighrHmischmshtmlTablehtmltoolshtmlwidgetsipredisobanditeratorsjomojquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvlme4lubridatemagrittrMASSMatrixmemoisemgcvmicemimeminqamitmlModelMetricsmunsellneuralnetnlmenloptrnnetnnlsnumDerivordinalpanparallellypillarpkgconfigplyrprettyunitspROCprodlimprogressprogressrproxypurrrR6randomForestrappdirsRColorBrewerRcppRcppEigenreadrrecipesreshape2rlangrmarkdownROCRrpartrstudioapisassscalesshapeSQUAREMstringistringrSuperLearnersurvivaltibbletidyrtidyselecttimechangetimeDatetinytextzdbucminfutf8vctrsviridisviridisLitevroomweightswithrxfunxgboostyaml