predict.LMCAnisCompo

Compute model variogram values
Evaluate the variogram model provided at some lag vectors

Support for geostatistical analysis of multivariate data,
in particular data with restrictions, e.g. positive amounts,
compositions, distributional data, microstructural data, etc.
It includes descriptive analysis and modelling for such data, both
from a two-point Gaussian perspective and multipoint perspective.
The methods mainly follow Tolosana-Delgado, Mueller and van den
Boogaart (2018) <doi:10.1007/s11004-018-9769-3>.

K Gerald van den Boogaart

gmGeostats

Geostatistics for Compositional Analysis

Raimon Tolosana-Delgado

Ute Mueller

K. Gerald van den Boogaart

Hassan Talebi

Helmholtz-Zentrum Dresden-Rossendorf 

Edith Cowan University 

predict.LMCAnisCompo function

<dl><dt>object</dt>
<dd>variogram model</dd>
<dt>newdata</dt>
<dd>matrix or data.frame of lag vectors</dd>
<dt>...</dt>
<dd>extra arguments for generic compatbility</dd></dl>

Arguments

Compute model variogram values

Evaluate the variogram model provided at some lag vectors — predict.LMCAnisCompo

<dl>

<dt>object</dt>
<dd>variogram model</dd>


<dt>newdata</dt>
<dd>matrix or data.frame of lag vectors</dd>


<dt>...</dt>
<dd>extra arguments for generic compatbility</dd>

</dl>

predict.LMCAnisCompo: Compute model variogram values
Evaluate the variogram model provided at some lag vectors

Description

Usage

Value

Arguments

Examples