Package: RESTK 1.0.0
Sergi Vilardell
RESTK: An Implementation of the RESTK Algorithm
Implementation of the RESTK algorithm based on Markov's Inequality from Vilardell, Sergi, Serra, Isabel, Mezzetti, Enrico, Abella, Jaume, Cazorla, Francisco J. and Del Castillo, J. (2022). "Using Markov's Inequality with Power-Of-k Function for Probabilistic WCET Estimation". In 34th Euromicro Conference on Real-Time Systems (ECRTS 2022). Leibniz International Proceedings in Informatics (LIPIcs) 231 20:1-20:24. <doi:10.4230/LIPIcs.ECRTS.2022.20>. This work has been supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773).
Authors:
RESTK_1.0.0.tar.gz
RESTK_1.0.0.tar.gz(r-4.5-noble)RESTK_1.0.0.tar.gz(r-4.4-noble)
RESTK_1.0.0.tgz(r-4.4-emscripten)RESTK_1.0.0.tgz(r-4.3-emscripten)
RESTK.pdf |RESTK.html✨
RESTK/json (API)
| # Install 'RESTK' in R: |
| install.packages('RESTK', 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 1 years agofrom:b450e37890. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 14 2024 |
| R-4.5-linux | OK | Dec 14 2024 |
Exports:compute_maxkestimate_quantiles_maxkget_min_maxklinear_adjustRESTKRESTK_trainingRESTK_validationsample_quantile_estimationtightness
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute the maximum k for a given sample | compute_maxk |
| Estimate Quantiles with Maxk | estimate_quantiles_maxk |
| Get the minimum maxk | get_min_maxk |
| Linear adjust | linear_adjust |
| RESTK | RESTK |
| RESTK Training | RESTK_training |
| RESTK Validation | RESTK_validation |
| Estimate Quantiles within the Sample | sample_quantile_estimation |
| Tightness function | tightness |