spsann: Optimization of Sample Configurations using Spatial Simulated Annealing

Methods to optimize sample configurations using spatial simulated annealing. Multiple objective functions are implemented for various purposes, such as variogram estimation, spatial trend estimation and spatial interpolation. A general purpose spatial simulated annealing function enables the user to define his/her own objective function. Solutions for augmenting existing sample configurations and solving multi-objective optimization problems are available as well.

Package details

AuthorAlessandro Samuel-Rosa [aut, cre], Lucia Helena Cunha dos Anjos [ths], Gustavo de Mattos Vasques [ths], Gerard B M Heuvelink [ths], Edzer Pebesma [ctb], Jon Skoien [ctb], Joshua French [ctb], Pierre Roudier [ctb], Dick Brus [ctb], Murray Lark [ctb]
MaintainerAlessandro Samuel-Rosa <[email protected]>
LicenseGPL (>= 2)
Version2.1-0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("spsann")

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spsann documentation built on June 23, 2017, 5:03 p.m.