Package: auRoc 0.2-1
Dai Feng
auRoc: Various Methods to Estimate the AUC
Estimate the AUC using a variety of methods as follows: (1) frequentist nonparametric methods based on the Mann-Whitney statistic or kernel methods. (2) frequentist parametric methods using the likelihood ratio test based on higher-order asymptotic results, the signed log-likelihood ratio test, the Wald test, or the approximate ''t'' solution to the Behrens-Fisher problem. (3) Bayesian parametric MCMC methods.
Authors:
auRoc_0.2-1.tar.gz
auRoc_0.2-1.tar.gz(r-4.5-noble)auRoc_0.2-1.tar.gz(r-4.4-noble)
auRoc_0.2-1.tgz(r-4.4-emscripten)auRoc_0.2-1.tgz(r-4.3-emscripten)
auRoc.pdf |auRoc.html✨
auRoc/json (API)
| # Install 'auRoc' in R: |
| install.packages('auRoc', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- petBrainGlioma - Standard Uptake Value (SUV) for Brain Glioma Grading
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:a631eed9e2. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 11 2024 |
| R-4.5-linux | OK | Dec 11 2024 |
Exports:auc.nonpara.kernelauc.nonpara.mwauc.para.bayesauc.para.frequentist
Dependencies:abindarmBHbootclicodadigestgluelatticelavaanlifecyclelme4MASSMatrixMBESSmiminqamnormtmvtnormnlmenloptrnumDerivOpenMxpbivnormProbYXquadprogRcppRcppEigenRcppParallelrjagsrlangrootSolverpfsemsemToolsStanHeaders
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| AUC by Kernel Methods | auc.nonpara.kernel |
| AUC Based on the Mann-Whitney Statistic | auc.nonpara.mw |
| AUC by the Bayesian MCMC | auc.para.bayes |
| AUC by Frequentist Parametric Methods | auc.para.frequentist |
| Standard Uptake Value (SUV) for Brain Glioma Grading | petBrainGlioma |
