| Name : R-BayesNSGP
| |
| Version : 0.1.2
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.12.2
| Date : 2024-06-14 11:57:28
|
| Group : Development/Libraries/Other
| Source RPM : R-BayesNSGP-0.1.2-lp153.12.2.src.rpm
|
| Size : 0.37 MB
| |
| Packager : (none)
| |
| Summary : Bayesian Analysis of Non-Stationary Gaussian Process Models
|
Description :
Enables off-the-shelf functionality for fully Bayesian, nonstationary
Gaussian process modeling. The approach to nonstationary modeling
involves a closed-form, convolution-based covariance function with
spatially-varying parameters; these parameter processes can be
specified either deterministically (using covariates or basis
functions) or stochastically (using approximate Gaussian processes).
Stationary Gaussian processes are a special case of our methodology,
and we furthermore implement approximate Gaussian process inference to
account for very large spatial data sets (Finley, et al (2017)
< arXiv:1702.00434v2>). Bayesian inference is carried out using Markov
chain Monte Carlo methods via the \'nimble\' package, and posterior
prediction for the Gaussian process at unobserved locations is provided
as a post-processing step.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
