R Bayesian Evidence Synthesis Tools
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. package
For introductory material, please refer to the vignettes which include
The main function of the package is gMAP. See it's help page for a detailed description of the statistical model.
| 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) | ||
RBesT.integrate_prob_eps | 1E-6 | probability mass left out from tails if integration needs to be restricted in range |
See NEWS.md file.
Stan Development Team (2020). RStan: the R interface to Stan. R package version 2.19.3. https://mc-stan.org
Useful links:
Maintainer : Sebastian Weber sebastian.weber@novartis.com
Other contributors: