Confidence and consistency: what are they and why using them? | Functions for calculating confidence and consistency | Workflow | Introduction | Data preparation | Training models and making predictions | Evaluation and interpretation | Evaluating multiple models
Package: confcons 0.3.2.9000
Ákos Bede-Fazekas
confcons: Confidence and Consistency of Predictive Distribution Models
Calculate confidence and consistency that measure the goodness-of-fit and transferability of predictive/potential distribution models (including species distribution models) as described by Somodi & Bede-Fazekas et al. (2024) <doi:10.1016/j.ecolmodel.2024.110667>.
Authors:
confcons_0.3.2.9000.tar.gz
confcons_0.3.2.9000.zip(r-4.7-any)confcons_0.3.2.9000.zip(r-4.6-any)confcons_0.3.2.9000.zip(r-4.5-any)
confcons_0.3.2.9000.tgz(r-4.6-any)confcons_0.3.2.9000.tgz(r-4.5-any)
confcons_0.3.2.9000.tar.gz(r-4.7-any)confcons_0.3.2.9000.tar.gz(r-4.6-any)
confcons_0.3.2.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
confcons/json (API)
| # Install 'confcons' in R: |
| install.packages('confcons', repos = c('https://bfakos.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bfakos/confcons/issues
Pkgdown/docs site:https://bfakos.github.io
Last updated from:5bd8ee4c88. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 192 | ||
| source / vignettes | OK | 291 | ||
| linux-release | OK | 218 | ||
| macos-release | OK | 160 | ||
| macos-oldrel | OK | 225 | ||
| windows-devel | OK | 104 | ||
| windows-release | OK | 99 | ||
| windows-oldrel | OK | 146 | ||
| wasm-release | OK | 166 |
Exports:confidenceconsistencymeasuresthresholds
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Confidence of the predictive distribution model | confidence |
| Consistency of the predictive distribution model | consistency |
| Goodness-of-fit, confidence and consistency measures | measures |
| Thresholds needed to create the extended confusion matrix | thresholds |