varcov

Calculate variance covariance matrix

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

varcov function

<dl><dt>sd_vector</dt>
<dd>vector of standard deviations.</dd>
<dt>cormat</dt>
<dd>correlation matrix.</dd></dl>

Arguments

Author

Calculate variance covariance matrix — varcov

<dl>

<dt>sd_vector</dt>
<dd>vector of standard deviations.</dd>


<dt>cormat</dt>
<dd>correlation matrix.</dd>

</dl>

varcov: Calculate variance covariance matrix

Description

Usage

Value

Arguments

Author

Examples