The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
For emulating multifidelity computer models. The major methods include univariate autoregressive cokriging and multivariate autoregressive cokriging. The autoregressive cokriging methods are implemented for both hierarchically nested design and non-nested design. For hierarchically nested design, the model parameters are estimated via standard optimization algorithms; For non-nested design, the model parameters are estimated via Monte Carlo expectation-maximization (MCEM) algorithms. In both cases, the priors are chosen such that the posterior distributions are proper. Notice that the uniform priors on range parameters in the correlation function lead to improper posteriors. This should be avoided when Bayesian analysis is adopted. The development of objective priors for autoregressive cokriging models can be found in Pulong Ma (2020) <doi:10.1137/19M1289893>. The development of the multivariate autoregressive cokriging models with possibly non-nested design can be found in Pulong Ma, Georgios Karagiannis, Bledar A Konomi, Taylor G Asher, Gabriel R Toro, and Andrew T Cox (2019) <doi:10.48550/arXiv.1909.01836>.
| Version: | 0.1.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp, mvtnorm (≥ 1.0-10), stats, methods, ggplot2 |
| LinkingTo: | Rcpp, RcppArmadillo, RcppEigen |
| Published: | 2021-12-02 |
| DOI: | 10.32614/CRAN.package.ARCokrig |
| Author: | Pulong Ma [aut, cre] |
| Maintainer: | Pulong Ma <mpulong at gmail.com> |
| BugReports: | https://github.com/pulongma/ARCokrig/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://CRAN.R-project.org/package=ARCokrig |
| NeedsCompilation: | yes |
| Citation: | ARCokrig citation info |
| Materials: | NEWS |
| CRAN checks: | ARCokrig results |
| Reference manual: | ARCokrig.pdf |
| Package source: | ARCokrig_0.1.2.tar.gz |
| Windows binaries: | r-devel: ARCokrig_0.1.2.zip, r-release: ARCokrig_0.1.2.zip, r-oldrel: ARCokrig_0.1.2.zip |
| macOS binaries: | r-release (arm64): ARCokrig_0.1.2.tgz, r-oldrel (arm64): ARCokrig_0.1.2.tgz, r-release (x86_64): ARCokrig_0.1.2.tgz, r-oldrel (x86_64): ARCokrig_0.1.2.tgz |
| Old sources: | ARCokrig archive |
Please use the canonical form https://CRAN.R-project.org/package=ARCokrig to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.