mean_MC_sgdf

Calculates mean from MC realizations for each location in a map.

Uncertainty propagation analysis in spatial environmental modelling following methodology
described in Heuvelink et al. (2007) <doi:10.1080/13658810601063951>
and Brown and Heuvelink (2007) <doi:10.1016/j.cageo.2006.06.015>. The package provides functions
for examining the uncertainty propagation starting from input data and model parameters,
via the environmental model onto model outputs. The functions include uncertainty model specification,
stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques.
Uncertain variables are described by probability distributions. Both numerical and categorical data types are handled.
Spatial auto-correlation within an attribute and cross-correlation between attributes is accommodated for.
The MC realizations may be used as input to the environmental models called from R, or externally.

Kasia Sawicka

spup

Spatial Uncertainty Propagation Analysis

Gerard Heuvelink

Dennis Walvoort

Stefan van Dam

Damiano Luzzi

mean_MC_sgdf function

<dl><dt>realizations</dt>
<dd>MC sample saved in SpatialGridDataFrame.</dd>
<dt>...</dt>
<dd>additional parameters.</dd></dl>

Arguments

Author

mean() function for MC sample saved in a SpatialGridDataFrame — mean_MC_sgdf

<dl>

<dt>realizations</dt>
<dd>MC sample saved in SpatialGridDataFrame.</dd>


<dt>...</dt>
<dd>additional parameters.</dd>

</dl>

mean_MC_sgdf: mean() function for MC sample saved in a SpatialGridDataFrame

Description

Usage

Value

Arguments

Author

Examples