Package: fpROC 0.1.0

fpROC: Fast Partial Receiver Operating Characteristic (ROC) Test for Ecological Niche Modeling
Provides optimized 'C++' code for computing the partial Receiver Operating Characteristic (ROC) test used in niche and species distribution modeling. The implementation follows Peterson et al. (2008) <doi:10.1016/j.ecolmodel.2007.11.008>. Parallelization via 'OpenMP' was implemented with assistance from the 'DeepSeek' Artificial Intelligence Assistant (<https://www.deepseek.com/>).
Authors:
fpROC_0.1.0.tar.gz
fpROC_0.1.0.zip(r-4.7)fpROC_0.1.0.zip(r-4.6)fpROC_0.1.0.zip(r-4.5)
fpROC_0.1.0.tgz(r-4.6-x86_64)fpROC_0.1.0.tgz(r-4.6-arm64)fpROC_0.1.0.tgz(r-4.5-x86_64)fpROC_0.1.0.tgz(r-4.5-arm64)
fpROC_0.1.0.tar.gz(r-4.7-arm64)fpROC_0.1.0.tar.gz(r-4.7-x86_64)fpROC_0.1.0.tar.gz(r-4.6-arm64)fpROC_0.1.0.tar.gz(r-4.6-x86_64)
fpROC_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
fpROC/json (API)
NEWS
| # Install 'fpROC' in R: |
| install.packages('fpROC', repos = c('https://luismurao.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/luismurao/fproc/issues
Pkgdown/docs site:https://luismurao.github.io
Last updated from:968b62119d. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 209 | ||
| linux-devel-x86_64 | OK | 209 | ||
| source / vignettes | OK | 196 | ||
| linux-release-arm64 | OK | 245 | ||
| linux-release-x86_64 | OK | 201 | ||
| macos-release-arm64 | OK | 167 | ||
| macos-release-x86_64 | OK | 331 | ||
| macos-oldrel-arm64 | OK | 165 | ||
| macos-oldrel-x86_64 | OK | 261 | ||
| windows-devel | OK | 179 | ||
| windows-release | OK | 167 | ||
| windows-oldrel | OK | 182 | ||
| wasm-release | OK | 118 |
Exports:auc_metricsauc_parallelsummarize_auc_resultstrap_roc
Dependencies:RcppRcppArmadilloterra
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calculate Partial and complete Area Under the Curve (AUC) Metrics | auc_metrics |
| Parallel AUC and partial AUC calculation with optimized memory usage | auc_parallel |
| Summarize Bootstrap AUC Results | summarize_auc_results |
| Calculate Area Under Curve (AUC) using trapezoidal rule | trap_roc |
