Package: RPIV 1.1.0

RPIV: Residual Prediction Tests for Well-Specification of Instrumental Variable Models

Two tests for the well-specification of the linear instrumental variable model. The first test is based on trying to predict the residuals of a two-stage least-squares regression using a random forest. The second test is robust to weak-identification and based on trying to predict the residuals for a particular candidate parameter and can also be used to construct confidence sets with an Anderson-Rubin-type inversion. Details can be found in Scheidegger, Londschien and Bühlmann (2025) "Machine-learning-powered specification testing in linear instrumental variable models" <doi:10.48550/arXiv.2506.12771>.

Authors:Cyrill Scheidegger [aut, cre, cph]

RPIV_1.1.0.tar.gz
RPIV_1.1.0.zip(r-4.7)RPIV_1.1.0.zip(r-4.6)RPIV_1.1.0.zip(r-4.5)
RPIV_1.1.0.tgz(r-4.6-any)RPIV_1.1.0.tgz(r-4.5-any)
RPIV_1.1.0.tar.gz(r-4.7-any)RPIV_1.1.0.tar.gz(r-4.6-any)
RPIV_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
RPIV/json (API)
NEWS

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

Bug tracker:https://github.com/cyrillsch/rpiv/issues

On CRAN:

Conda:

3.90 score 2 stars 6 scripts 473 downloads 2 exports 5 dependencies

Last updated from:4e96259d9e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK128
source / vignettesOK164
linux-release-x86_64OK130
macos-release-arm64OK82
macos-oldrel-arm64OK87
windows-develOK80
windows-releaseOK84
windows-oldrelOK89
wasm-releaseOK92

Exports:RPIV_testweak_RPIV_test

Dependencies:latticeMatrixrangerRcppRcppEigen