spsann: Optimization of Sample Configurations using Spatial Simulated Annealing
Version 2.1-0

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]
Date of publication2017-06-23 13:40:59 UTC
MaintainerAlessandro Samuel-Rosa <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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spsann documentation built on June 23, 2017, 5:03 p.m.