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.
Details
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.
Global Options
| 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.save_warmup | FALSE | MCMC warmup samples saving |
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, | adaptive integration of densities (used when | |
rel.tol=.Machine$double.eps^0.25, | RBesT.integrate_method is "adaptive" | |
abs.tol=.Machine$double.eps^0.25, | or for non-normMix densities) | |
subdivisions=1E3) | ||
RBesT.integrate_prob_eps | 1E-6 | probability mass left out from tails if integration needs to be restricted in range |
RBesT.integrate_method | "GQ" | integration method for mixture densities: "GQ" (Gaussian quadrature, deterministic) or "adaptive" (adaptive Gauss-Kronrod). GQ uses Gauss-Hermite for normMix, Gauss-Jacobi for betaMix, and Gauss-Laguerre for gammaMix. |
RBesT.GQ_nodes | 20 | starting number of Gaussian quadrature nodes (only used when RBesT.integrate_method is "GQ") |
RBesT.GQ_rel_tol | 1E-4 | relative tolerance target for GQ refinement; the node count is increased until successive estimates agree within max(RBesT.GQ_abs_tol, RBesT.GQ_rel_tol * |I|). Set to a non-finite or non-positive value (e.g. Inf) to disable refinement (single evaluation at RBesT.GQ_nodes). |
RBesT.GQ_abs_tol | 1E-6 | absolute tolerance floor for GQ refinement |
RBesT.GQ_max_nodes | 240 | upper cap on the GQ node count during refinement |
RBesT.GQ_node_growth | 2 | multiplicative growth factor for the GQ node count between refinement steps |
RBesT.GQ_on_nonconvergence | "adaptive" | behaviour when GQ refinement reaches RBesT.GQ_max_nodes without meeting tolerance: "adaptive" (fall through to adaptive integration), "warn" (warn and return best estimate), "error", or "silent" |
References
Stan Development Team (2020). RStan: the R interface to Stan. R package version 2.19.3. https://mc-stan.org
Author
Maintainer: Sebastian Weber sebastian.weber@novartis.com
Authors:
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]
Lukas A. Widmer lukas_andreas.widmer@novartis.com (ORCID) [contributor]
Daniel Sabanés Bové daniel.sabanes_bove@rconis.com (ORCID) [contributor]
Trustees of Columbia University (R/stanmodels.R, configure, configure.win) [copyright holder]