Package: RRI 1.1

Panos Toulis

RRI: Residual Randomization Inference for Regression Models

Testing and inference for regression models using residual randomization methods. The basis of inference is an invariance assumption on the regression errors, e.g., clustered errors, or doubly-clustered errors.

Authors:Panos Toulis

RRI_1.1.tar.gz
RRI_1.1.tar.gz(r-4.7-arm64)RRI_1.1.tar.gz(r-4.7-x86_64)RRI_1.1.tar.gz(r-4.6-arm64)RRI_1.1.tar.gz(r-4.6-x86_64)
RRI_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
RRI/json (API)

# Install 'RRI' in R:
install.packages('RRI', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.00 score 176 downloads 1 mentions 16 exports 2 dependencies

Last updated from:8986bd63ce. Checks:4 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE128
linux-devel-x86_64NOTE114
source / vignettesOK232
linux-release-arm64NOTE140
linux-release-x86_64NOTE122
wasm-releaseOK103

Exports:check_modelexample_clusteringexample_modelfastLmget_clustered_epsOLS_cone_sided_testout_pvalr_test_crestricted_OLS_crrinfrrinf_clustrrinfBaserrtestrrtest_clusttwo_sided_test

Dependencies:RcppRcppArmadillo