Construction and smart selection of Gaussian process models with emphasis on treatment of functional inputs. This package offers: (i) flexible modeling of functionalinput regression problems through the fairly general Gaussian process model; (ii) builtin dimension reduction for functional inputs; (iii) heuristic optimization of the structural parameters of the model (e.g., active inputs, kernel function, type of distance). Metamodeling background is provided in Betancourt et al. (2020) <doi:10.1016/j.ress.2020.106870>. The algorithm for structural parameter optimization is described in <https://hal.archivesouvertes.fr/hal02532713>.
Package details 


Author  Jose Betancourt [cre, aut], François Bachoc [aut], Thierry Klein [aut], Deborah Idier [ctb], Jeremy Rohmer [ctb] 
Maintainer  Jose Betancourt <djbetancourt@uninorte.edu.co> 
License  GPL3 
Version  0.2.2 
URL  https://djbetancourtgh.github.io/funGp/ 
Package repository  View on CRAN 
Installation 
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