Residual Prediction Tests for Well-Specification of Instrumental Variable Models R package RPIV version 1.1.0 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>. Software Imports: ranger, stats Suggests: testthat (>= 3.0.0) Cyrill Scheidegger <cyrill.scheidegger@stat.math.ethz.ch> Comprehensive R Archive Network (CRAN) Cyrill Scheidegger [aut, cre, cph] (ORCID: <https://orcid.org/0009-0005-2851-1384>) GPL (>= 3) 2026-03-24 application/tgz https://CRAN.R-project.org/package=RPIV doi:10.32614/CRAN.package.RPIV