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spsann (version 1.0-2)

Optimization of Sample Configurations using Spatial Simulated Annealing

Description

Methods to optimize sample configurations using spatial simulated annealing. Multiple objective functions are implemented for various purposes, such as variogram estimation, trend estimation, and spatial interpolation. A general purpose spatial simulated annealing function enables the user to define his/her own objective function.

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Version

Install

install.packages('spsann')

Monthly Downloads

11

Version

1.0-2

License

GPL (>= 2)

Maintainer

Alessandro SamuelRosa

Last Published

October 25th, 2015

Functions in spsann (1.0-2)

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
spsann-package

spsann: Optimization of Sample Configurations using Spatial Simulated Annealing
optimSPAN

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

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

Optimization of sample configurations for spatial interpolation
optimMKV

Optimization of sample configurations for spatial interpolation
objSPSANN

Auxiliary tools
optimDIST

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

Random perturbation of spatial points