Package: prototest 1.2
Stephen Reid
prototest: Inference on Prototypes from Clusters of Features
Procedures for testing for group-wide signal in clusters of variables. Tests can be performed for single groups in isolation (univariate) or multiple groups together (multivariate). Specific tests include the exact and approximate (un)selective likelihood ratio tests described in Reid et al (2015), the selective F test and marginal screening prototype test of Reid and Tibshirani (2015). User may pre-specify columns to be included in prototype formation, or allow the function to select them itself. A mixture of these two is also possible. Any variable selection is accounted for using the selective inference framework. Options for non-sampling and hit-and-run null reference distributions.
Authors:
prototest_1.2.tar.gz
prototest_1.2.tar.gz(r-4.5-noble)prototest_1.2.tar.gz(r-4.4-noble)
prototest_1.2.tgz(r-4.4-emscripten)prototest_1.2.tgz(r-4.3-emscripten)
prototest.pdf |prototest.html✨
prototest/json (API)
# Install 'prototest' in R: |
install.packages('prototest', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:77a612e659. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 22 2024 |
R-4.5-linux-x86_64 | NOTE | Dec 22 2024 |
Exports:prototest.multivariateprototest.univariate
Dependencies:codetoolsforeachglmnetintervalsiteratorslatticeMASSMatrixRcppRcppArmadilloRcppEigenshapesurvival
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Inference on Prototypes from Clusters of Features | prototest-package prototest |
Print 'prototest' object | print.prototest |
Perform Prototype or F tests for Significance of Groups of Predictors in the Multivariate Model | prototest.multivariate |
Perform Prototype or F Tests for Significance of Groups of Predictors in the Univariate Model | prototest.univariate |