minimalDistance

krigingVariance

<code>SpatialDataFrame</code> (not "SpatialIndexDataFrame"), for each of the locations a cost is computed

allLocations

indices of sensors in <code>allLocations</code>

locations

<code>model</code> to be forwarded to <code><a rd-options="gstat" href="/link/krige?package=sensors4plumes&version=0.9.3&to=gstat" data-mini-rdoc="gstat::krige">krige</a></code>

model

<code>character</code> to be forwarded as <code>algorithm</code> to <code><a rd-options="FNN" href="/link/get.knnx?package=sensors4plumes&version=0.9.3&to=FNN" data-mini-rdoc="FNN::get.knnx">get.knnx</a></code>

algorithm

<code>Kriging variance</code> computes the ordinary kriging variance at a given set of points for the case of certain sensor locations and variogram model.<code>minimalDistance</code> computes for each given point the distance to the next sensor.
Both functions can be used as input to <code>spatialSpread</code> that runs them and turns the result into global cost.

spatialSpreadFunctions

Test sampling designs by several flexible cost functions, usually based on the simulations, and optimise sampling designs using different optimisation algorithms; load plume simulations (on lattice or points) even if they do not fit into memory.

Kristina Helle

sensors4plumes

Test and Optimise Sampling Designs Based on Plume Simulations

spatialSpreadFunctions function

<code>model</code> to be forwarded to <code><a rd-options='gstat' href='krige'>krige</a></code>

<code>character</code> to be forwarded as <code>algorithm</code> to <code><a rd-options='FNN' href='get.knnx'>get.knnx</a></code>

spatialSpreadFunctions: Cost functions dependent only on sensor locations

Description

Usage

Arguments

Value

Examples