Package: ed50 0.1.1
ed50: Estimate ED50 and Its Confidence Interval
Functions of five estimation method for ED50 (50 percent effective dose) are provided, and they are respectively Dixon-Mood method (1948) <doi:10.2307/2280071>, Choi's original turning point method (1990) <doi:10.2307/2531453> and it's modified version given by us, as well as logistic regression and isotonic regression. Besides, the package also supports comparison between two estimation results.
Authors:
ed50_0.1.1.tar.gz
ed50_0.1.1.zip(r-4.5)ed50_0.1.1.zip(r-4.4)ed50_0.1.1.zip(r-4.3)
ed50_0.1.1.tgz(r-4.4-any)ed50_0.1.1.tgz(r-4.3-any)
ed50_0.1.1.tar.gz(r-4.5-noble)ed50_0.1.1.tar.gz(r-4.4-noble)
ed50_0.1.1.tgz(r-4.4-emscripten)ed50_0.1.1.tgz(r-4.3-emscripten)
ed50.pdf |ed50.html✨
ed50/json (API)
| # Install 'ed50' in R: |
| install.packages('ed50', repos = c('https://mousieur-g.r-universe.dev', 'https://cloud.r-project.org')) |
- gTableOrigin - G Table
- groupS - A Real Experiment Dose Data
- groupSN - A Real Experiment Dose Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:a78970e095. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 13 2024 |
| R-4.5-win | OK | Oct 13 2024 |
| R-4.5-linux | OK | Oct 13 2024 |
| R-4.4-win | OK | Oct 13 2024 |
| R-4.4-mac | OK | Oct 13 2024 |
| R-4.3-win | OK | Oct 13 2024 |
| R-4.3-mac | OK | Oct 13 2024 |
Exports:bootBC.cibootIsotonicRegressionbootIsotonicResamplecompareestimategenerateDatapreparePava
Dependencies:boot
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Estimate Confidence Interval of ED50 Using Isotonic Regression | bootBC.ci |
| Isotonic Regression Function | bootIsotonicRegression |
| The resample function of isotonic regression | bootIsotonicResample |
| Compare ED50 Estimation of Independent Two-sample Case | compare |
| Estimate ED50 | estimate |
| Generate Simulation Data of Up-and-Down Experiment | generateData |
| A Real Experiment Dose Data | groupS |
| A Real Experiment Dose Data | groupSN |
| G Table | gTableOrigin |
| Covert Data Using PAVA Algorithm | preparePava |
