| Name : R-MCMChybridGP
| |
| Version : 5.4
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.13
| Date : 2024-06-14 11:03:05
|
| Group : Development/Libraries/Other
| Source RPM : R-MCMChybridGP-5.4-lp153.2.13.src.rpm
|
| Size : 0.11 MB
| |
| Packager : (none)
| |
| Summary : Hybrid Markov Chain Monte Carlo using Gaussian Processes
|
Description :
Hybrid Markov chain Monte Carlo (MCMC) to simulate from a multimodal
target distribution. A Gaussian process approximation makes this
possible when derivatives are unknown. The Package serves to minimize
the number of function evaluations in Bayesian calibration of computer
models using parallel tempering. It allows replacement of the true
target distribution in high temperature chains, or complete replacement
of the target. Methods used are described in, \"Efficient MCMC schemes
for computationally expensive posterior distributions\", Fielding et al.
(2011) < doi:10.1198/TECH.2010.09195>. The research presented in this
work was carried out as part of the Singapore-Delft Water Alliance
Multi-Objective Multi-Reservoir Management research programme
(R-264-001-272).
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
