Package: TSCI 3.0.5

David Carl

TSCI: Tools for Causal Inference with Possibly Invalid Instrumental Variables

Two stage curvature identification with machine learning for causal inference in settings when instrumental variable regression is not suitable because of potentially invalid instrumental variables. Based on Guo and Buehlmann (2022) "Two Stage Curvature Identification with Machine Learning: Causal Inference with Possibly Invalid Instrumental Variables" <doi:10.48550/arXiv.2203.12808>. The vignette is available in Carl, Emmenegger, Bühlmann and Guo (2025) "TSCI: Two Stage Curvature Identification for Causal Inference with Invalid Instruments in R" <doi:10.18637/jss.v114.i07>.

Authors:David Carl [aut, cre], Corinne Emmenegger [aut], Wei Yuan [aut], Mengchu Zheng [aut], Zijian Guo [aut]

TSCI_3.0.5.tar.gz
TSCI_3.0.5.zip(r-4.7)TSCI_3.0.5.zip(r-4.6)TSCI_3.0.5.zip(r-4.5)
TSCI_3.0.5.tgz(r-4.6-any)TSCI_3.0.5.tgz(r-4.5-any)
TSCI_3.0.5.tar.gz(r-4.7-any)TSCI_3.0.5.tar.gz(r-4.6-any)
TSCI_3.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
TSCI/json (API)

# Install 'TSCI' in R:
install.packages('TSCI', repos = c('https://dlcarl.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/dlcarl/tsci/issues

On CRAN:

Conda:

3.00 score 1 stars 3 scripts 616 downloads 6 exports 25 dependencies

Last updated from:bd894dc62e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK180
source / vignettesOK183
linux-release-x86_64OK217
macos-release-arm64OK179
macos-oldrel-arm64OK198
windows-develOK116
windows-releaseOK108
windows-oldrelOK95
wasm-releaseOK121

Exports:create_interactionscreate_monomialstsci_boostingtsci_foresttsci_polytsci_secondstage

Dependencies:clidata.tablefastDummiesgluejsonlitelatticelifecyclemagrittrMatrixpillarpkgconfigrangerRcppRcppArmadilloRcppEigenRcppParallelRfastrlangstringistringrtibbleutf8vctrsxgboostzigg