distribution_sampling_raster

Only used in samplemethod "randomSampling" for MarginalNumericSpatial.

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

distribution_sampling_raster function

<dl><dt>distribution</dt>
<dd>A string describing selected distribution. The same as a part of
the string following the "r" in each random variate generation function in ?distributions.</dd>
<dt>parameters_stack</dt>
<dd>parameters to pass to the random variate generation function after
number of observations.</dd></dl>

Arguments

Author

Sampling from a given distribution — distribution_sampling_raster

<dl>

<dt>distribution</dt>
<dd>A string describing selected distribution. The same as a part of
the string following the "r" in each random variate generation function in ?distributions.</dd>


<dt>parameters_stack</dt>
<dd>parameters to pass to the random variate generation function after
number of observations.</dd>

</dl>

distribution_sampling_raster: Sampling from a given distribution

Description

Usage

Value

Arguments

Author