DynamicGP: Modelling and Analysis of Dynamic Computer Experiments

Emulating and solving inverse problems for dynamic computer experiments. It contains two major functionalities: (1) localized GP model for large-scale dynamic computer experiments using the algorithm proposed by Zhang et al. (2018) <arXiv:1611.09488>; (2) solving inverse problems in dynamic computer experiments. The current version only supports 64-bit version of R.

Package details

AuthorRu Zhang [aut, cre], Chunfang Devon Lin [aut], Pritam Ranjan [aut], Robert B Gramacy [ctb], Nicolas Devillard [ctb], Jorge Nocedal [ctb], Jose Luis Morales [ctb], Ciyou Zhu [ctb], Richard Byrd [ctb], Peihuang Lu-Chen [ctb], Berend Hasselman [ctb], Jack Dongarra [ctb], Jeremy Du Croz [ctb], Sven Hammarling [ctb], Richard Hanson [ctb], University of Chicago [cph], University of California [cph]
MaintainerRu Zhang <[email protected]>
LicenseGPL (>= 2)
Version1.1-5
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("DynamicGP")

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DynamicGP documentation built on Nov. 19, 2019, 9:06 a.m.