Package: APPEstimation 0.1.1
APPEstimation: Adjusted Prediction Model Performance Estimation
Calculating predictive model performance measures adjusted for predictor distributions using density ratio method (Sugiyama et al., (2012, ISBN:9781139035613)). L1 and L2 error for continuous outcome and C-statistics for binomial outcome are computed.
Authors:
APPEstimation_0.1.1.tar.gz
APPEstimation_0.1.1.zip(r-4.5)APPEstimation_0.1.1.zip(r-4.4)APPEstimation_0.1.1.zip(r-4.3)
APPEstimation_0.1.1.tgz(r-4.4-any)APPEstimation_0.1.1.tgz(r-4.3-any)
APPEstimation_0.1.1.tar.gz(r-4.5-noble)APPEstimation_0.1.1.tar.gz(r-4.4-noble)
APPEstimation_0.1.1.tgz(r-4.4-emscripten)APPEstimation_0.1.1.tgz(r-4.3-emscripten)
APPEstimation.pdf |APPEstimation.html✨
APPEstimation/json (API)
| # Install 'APPEstimation' in R: |
| install.packages('APPEstimation', repos = c('https://eisuke-inoue.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 7 years agofrom:9fedeba12a. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 23 2024 |
| R-4.5-win | OK | Nov 23 2024 |
| R-4.5-linux | OK | Nov 23 2024 |
| R-4.4-win | OK | Nov 23 2024 |
| R-4.4-mac | OK | Nov 23 2024 |
| R-4.3-win | OK | Nov 23 2024 |
| R-4.3-mac | OK | Nov 23 2024 |
Exports:appe.glmappe.lmcvalest.bindensratio.appe
Dependencies:densratio
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| R function to calculate model performance measure adjusted for predictor distributions. | APPEstimation-package APPEstimation |
| C-statistics adjusted for predictor distributions | appe.glm |
| L_1 and L_2 errors adjusted for predictor distributions | appe.lm |
| Estimation of C-statistics | cvalest.bin |
| A wrapper function | densratio.appe |
