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.

Version: 2.2.0
Imports: methods, pedometrics, Rcpp, sp, SpatialTools
LinkingTo: Rcpp
Suggests: gstat, tcltk, knitr
Published: 2019-04-29
Author: Alessandro Samuel-Rosa ORCID iD [aut, cre], Lucia Helena Cunha dos Anjos ORCID iD [ths], Gustavo de Mattos Vasques [ths], Gerard B M Heuvelink ORCID iD [ths], Dick Brus ORCID iD [ctb], Richard Murray Lark ORCID iD [ctb], Edzer Pebesma ORCID iD [ctb], Jon Skoien [ctb], Joshua French [ctb], Pierre Roudier [ctb]
Maintainer: Alessandro Samuel-Rosa <alessandrosamuelrosa at gmail.com>
BugReports: https://github.com/samuel-rosa/spsann/issues/
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/samuel-rosa/spsann/
NeedsCompilation: yes
Language: en-GB
Materials: README NEWS
In views: Spatial
CRAN checks: spsann results

Downloads:

Reference manual: spsann.pdf
Vignettes: spsann: Optimization of Sample Configurations Using Spatial Simulated Annealing
Package source: spsann_2.2.0.tar.gz
Windows binaries: r-prerelease: spsann_2.2.0.zip, r-release: spsann_2.2.0.zip, r-oldrel: spsann_2.2.0.zip
macOS binaries: r-prerelease: spsann_2.2.0.tgz, r-release: spsann_2.2.0.tgz, r-oldrel: spsann_2.2.0.tgz
Old sources: spsann archive

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