Package: MarginalMaxTest 1.0.1

MarginalMaxTest: Max-Type Test for Marginal Correlation with Bootstrap

Test the marginal correlation between a scalar response variable with a vector of explanatory variables using the max-type test with bootstrap. The test is based on the max-type statistic and its asymptotic distribution under the null hypothesis of no marginal correlation. The bootstrap procedure is used to approximate the null distribution of the test statistic. The package provides a function for performing the test. For more technical details, refer to Zhang and Laber (2014) <doi:10.1080/01621459.2015.1106403>.

Authors:Canyi Chen [aut, cre, cph]

MarginalMaxTest_1.0.1.tar.gz
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MarginalMaxTest_1.0.1.tgz(r-4.6-x86_64)MarginalMaxTest_1.0.1.tgz(r-4.6-arm64)MarginalMaxTest_1.0.1.tgz(r-4.5-x86_64)MarginalMaxTest_1.0.1.tgz(r-4.5-arm64)
MarginalMaxTest_1.0.1.tar.gz(r-4.7-arm64)MarginalMaxTest_1.0.1.tar.gz(r-4.7-x86_64)MarginalMaxTest_1.0.1.tar.gz(r-4.6-arm64)MarginalMaxTest_1.0.1.tar.gz(r-4.6-x86_64)
MarginalMaxTest_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
MarginalMaxTest/json (API)
NEWS

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

Bug tracker:https://github.com/canyi-chen/marginalmaxtest/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

2.70 score 2 scripts 179 downloads 1 exports 2 dependencies

Last updated from:5aaec00b2f. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK133
linux-devel-x86_64OK139
source / vignettesOK163
linux-release-arm64OK127
linux-release-x86_64OK171
macos-release-arm64OK160
macos-release-x86_64OK443
macos-oldrel-arm64OK169
macos-oldrel-x86_64OK294
windows-develOK119
windows-releaseOK96
windows-oldrelOK106
wasm-releaseOK132

Exports:marginal.test

Dependencies:RcppRcppArmadillo