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Optimization of Sample Configurations using Spatial Simulated Annealing

Installation

The spsann package was created to help you creating optimum spatial sample configurations using the power of spatial simulated annealing. It can be downloaded from CRAN using:

install.packages(pkgs = "spsann")

The development version of spsann, available at GitHub, can be downloaded -- using the devtools package -- with:

if (!require(devtools)) {
  install.packages(pkgs = "devtools")
}
devtools::install_github("samuel-rosa/spsann")

How to collaborate

We use the fork & pull collaborative development model. This means that you are free to make a parallel copy of this repository, change the source code as you see fit, and then push the changes to your personal copy of this repository. All this without requiring any authorization. If the changes you've made to your personal copy of this repository are interesting and you're willing to share them with us, then just have them pulled -- pull request -- to this repository. After reviewing the changes, we will decide whether they can be merged -- merge -- with the source code of this repository.

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Version

Install

install.packages('spsann')

Monthly Downloads

69

Version

2.2.0

License

GPL (>= 2)

Issues

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Last Published

April 29th, 2019

Functions in spsann (2.2.0)

optimDIST

Optimization of sample configurations for spatial trend identification and estimation (II)
objSPSANN

Auxiliary tools
optimCLHS

Optimization of sample configurations for spatial trend identification and estimation (IV)
minmaxPareto

Pareto minimum and maximum values
spsann-package

The spsann Package
plot.OptimizedSampleConfiguration

Plot an optimized sample configuration
optimACDC

Optimization of sample configurations for spatial trend identification and estimation (III)
optimCORR

Optimization of sample configurations for spatial trend identification and estimation (I)
optimUSER

Optimization of sample configurations using a user-defined objective function
optimPPL

Optimization of sample configurations for variogram identification and estimation
optimSPAN

Optimization of sample configurations for variogram and spatial trend identification and estimation, and for spatial interpolation
optimMKV

Optimization of sample configurations for spatial interpolation (II)
scheduleSPSANN

spsann annealing schedule
spJitter

Random perturbation of spatial points
optimMSSD

Optimization of sample configurations for spatial interpolation (I)