Package: EKMCMC 1.1.2
EKMCMC: MCMC Procedures for Estimating Enzyme Kinetics Constants
Functions for estimating catalytic constant and Michaelis-Menten constant for enzyme kinetics model using Metropolis-Hasting algorithm within Gibbs sampler based on the Bayesian framework.
Authors:
EKMCMC_1.1.2.tar.gz
EKMCMC_1.1.2.zip(r-4.5)EKMCMC_1.1.2.zip(r-4.4)EKMCMC_1.1.2.zip(r-4.3)
EKMCMC_1.1.2.tgz(r-4.4-any)EKMCMC_1.1.2.tgz(r-4.3-any)
EKMCMC_1.1.2.tar.gz(r-4.5-noble)EKMCMC_1.1.2.tar.gz(r-4.4-noble)
EKMCMC_1.1.2.tgz(r-4.4-emscripten)EKMCMC_1.1.2.tgz(r-4.3-emscripten)
EKMCMC.pdf |EKMCMC.html✨
EKMCMC/json (API)
| # Install 'EKMCMC' in R: |
| install.packages('EKMCMC', repos = c('https://hyukpyohong.r-universe.dev', 'https://cloud.r-project.org')) |
- timeseries_data_example - Product concentration of 101 observed time with different initial conditions
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:adb61ee678. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 16 2024 |
| R-4.5-win | OK | Sep 16 2024 |
| R-4.5-linux | OK | Sep 16 2024 |
| R-4.4-win | OK | Sep 16 2024 |
| R-4.4-mac | OK | Sep 16 2024 |
| R-4.3-win | OK | Sep 16 2024 |
| R-4.3-mac | OK | Sep 16 2024 |
Exports:catalytic_estmain_estMM_catal_estMM_est
Dependencies:numDeriv
