Package: auRoc 0.2-1

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:Dai Feng [aut, cre], Damjan Manevski [auc], Maja Pohar Perme [auc]

auRoc_0.2-1.tar.gz
auRoc_0.2-1.zip(r-4.7)auRoc_0.2-1.zip(r-4.6)auRoc_0.2-1.zip(r-4.5)
auRoc_0.2-1.tgz(r-4.6-any)auRoc_0.2-1.tgz(r-4.5-any)
auRoc_0.2-1.tar.gz(r-4.7-any)auRoc_0.2-1.tar.gz(r-4.6-any)
auRoc_0.2-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
auRoc/json (API)

# Install 'auRoc' in R:

install.packages('auRoc', repos = c('https://daifengstat.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
c++– GNU Standard C++ Library v3

Datasets:

petBrainGlioma - Standard Uptake Value (SUV) for Brain Glioma Grading

On CRAN:

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

jags cpp

1.00 score 4 scripts 261 downloads 1 mentions 4 exports 38 dependencies

Last updated from:a631eed9e2. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	154
source / vignettes	OK	162
linux-release-x86_64	OK	128
macos-release-arm64	OK	115
macos-oldrel-arm64	OK	74
windows-devel	OK	117
windows-release	OK	105
windows-oldrel	OK	83
wasm-release	OK	134

Exports:auc.nonpara.kernel auc.nonpara.mw auc.para.bayes auc.para.frequentist

Dependencies:abind arm BH boot cli coda digest lattice lavaan lifecycle lme4 MASS Matrix MBESS mi minqa mnormt mvtnorm nlme nloptr numDeriv OpenMx pbivnorm ProbYX quadprog rbibutils Rcpp RcppEigen RcppParallel Rdpack reformulas rjags rlang rootSolve rpf sem semTools StanHeaders

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

Package: auRoc 0.2-1

auRoc: Various Methods to Estimate the AUC

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)