Authors | Introduction | Functions in the R package | Uses of the Performance Metrics | Reference
Package: PerMat 0.1.0
Pankaj Das
PerMat: Performance Metrics in Predictive Modeling
Performance metric provides different performance measures like mean squared error, root mean square error, mean absolute deviation, mean absolute percentage error etc. of a fitted model. These can provide a way for forecasters to quantitatively compare the performance of competing models. For method details see (i) Pankaj Das (2020) <http://krishi.icar.gov.in/jspui/handle/123456789/44138>.
Authors:
PerMat_0.1.0.tar.gz
PerMat_0.1.0.tar.gz(r-4.7-any)PerMat_0.1.0.tar.gz(r-4.6-any)
PerMat_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
PerMat/json (API)
| # Install 'PerMat' in R: |
| install.packages('PerMat', 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 from:81141a6e95. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 112 | ||
| source / vignettes | OK | 209 | ||
| linux-release-x86_64 | OK | 116 | ||
| wasm-release | OK | 97 |
Exports:accuracyCVRMSEMAEMAPEMENRMSER2RMSE
Dependencies:
