Package: OneStep 0.9.4
OneStep: One-Step Estimation
Provide principally an eponymic function that numerically computes the Le Cam's one-step estimator for an independent and identically distributed sample. One-step estimation is asymptotically efficient (see L. Le Cam (1956) <https://projecteuclid.org/euclid.bsmsp/1200501652>) and can be computed faster than the maximum likelihood estimator for large observation samples, see e.g. Brouste et al. (2021) <doi:10.32614/RJ-2021-044>.
Authors:
OneStep_0.9.4.tar.gz
OneStep_0.9.4.zip(r-4.5)OneStep_0.9.4.zip(r-4.4)OneStep_0.9.4.zip(r-4.3)
OneStep_0.9.4.tgz(r-4.4-any)OneStep_0.9.4.tgz(r-4.3-any)
OneStep_0.9.4.tar.gz(r-4.5-noble)OneStep_0.9.4.tar.gz(r-4.4-noble)
OneStep_0.9.4.tgz(r-4.4-emscripten)OneStep_0.9.4.tgz(r-4.3-emscripten)
OneStep.pdf |OneStep.html✨
OneStep/json (API)
NEWS
| # Install 'OneStep' in R: |
| install.packages('OneStep', repos = c('https://dutangc.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 1 months agofrom:42fd01175d. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 17 2024 |
| R-4.5-win | OK | Nov 17 2024 |
| R-4.5-linux | OK | Nov 17 2024 |
| R-4.4-win | OK | Nov 17 2024 |
| R-4.4-mac | OK | Nov 17 2024 |
| R-4.3-win | OK | Nov 17 2024 |
| R-4.3-mac | OK | Nov 17 2024 |
Exports:benchonestepbenchonestep.replicateonestep
Dependencies:extraDistrfitdistrpluslatticeMASSMatrixnumDerivRcpprlangsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| One-Step Estimation | OneStep-package OneStep |
| Performing benchmark of one-step MLE against other methods | benchonestep benchonestep.replicate |
| Executing Le Cam's one-step estimation | onestep |
