The RBesT tools are designed to support in the derivation of parametric informative priors, asses design characeristics and perform analyses. Supported endpoints include normal, binary and Poisson.
| Option | Default | Description |
RBesT.MC.warmup | 2000 | MCMC warmup iterations |
RBesT.MC.iter | 6000 | total MCMC iterations |
RBesT.MC.chains | 4 | MCMC chains |
RBesT.MC.thin | 4 | MCMC thinning |
RBesT.MC.control | list(adapt_delta=0.99, | sets control argument for Stan call |
stepsize=0.01, | ||
max_treedepth=20) | ||
RBesT.MC.ncp | 1 | parametrization: 0=CP, 1=NCP, 2=Automatic |
RBesT.MC.init | 1 | range of initial uniform [-1,1] is the default |
RBesT.MC.rescale | TRUE | Automatic rescaling of raw parameters |
RBesT.verbose | FALSE | requests outputs to be more verbose |
RBesT.integrate_args | list(lower=-Inf, | arguments passed to integrate for |
upper=Inf, | intergation of densities | |
rel.tol=.Machine$double.eps^0.25, | ||
abs.tol=.Machine$double.eps^0.25, | ||
subdivisions=1E3) |
See NEWS.md file.
Maintainer: Sebastian Weber sebastian.weber@novartis.com
Other contributors:
Novartis Pharma AG [copyright holder]
Beat Neuenschwander beat.neuenschwander@novartis.com [contributor]
Heinz Schmidli heinz.schmidli@novartis.com [contributor]
Baldur Magnusson baldur.magnusson@novartis.com [contributor]
Yue Li yue-1.li@novartis.com [contributor]
Satrajit Roychoudhury satrajit.roychoudhury@novartis.com [contributor]
Trustees of Columbia University (R/stanmodels.R, configure, configure.win) [copyright holder]
For introductory material, please refer to the vignettes which include
Introduction (binary)
Introduction (normal)
Customizing RBesT Plots
Robust MAP, advanced usage
The main function of the package is gMAP. See it's
help page for a detailed description of the statistical model.
Stan Development Team (2020). RStan: the R interface to Stan. R package version 2.19.3. https://mc-stan.org
Useful links: