mGstat : A Geostatistical Matlab toolbox
Download
Stable version
The latest stable version of mGstat can be downloaded from here:
Development version
Development of mGstat is managed using git hosted at GitHub.
The developmnet code can be cloned using:
git clone https://github.com/cultpenguin/mGstat.git mGstat
or a zip-archive can be obtained from
mGstat_git_master.zip
Documentation
mGstat user guide : [PDF] [HTML]
Introduction
mGstat aims to be a geostatistical toolbox for Matlab.
It provides
Native kriging kriging algorithms
Simple kriging, ordinary kriging and Universial/Kriging with a trend are available. All methods support data observations in ND-space. Thus, for example Time-Space kriging can be used.
Synthetic semivariogram can be calculated using both GSLIB and GSTAT syntax.
Experimental semivariograms can be calculated from data observations.
[.. more info in the manual]
An interface to GSTAT
mGstat provides an interface to GSTAT[www], which is a popular open source computer code for multivariate geostatistical modelling.
The interface enable one to call gstat and have the output returned seamlessly into Matlab.
The interface makes it straightforward to call GSTAT using Matlab as a scripting language.
[..more info in the manual]
An interface to VISIM
VISIM[www] is a GSLIB style program that can be used to solve linear inverse problems, using either Sequential Gaussian Simulation or Direct Sequential Simulation (with histogram reproduction) conditioned to noisy block data.
It can also function as a conventional point based simulation algorithm.
The mGstat interface enables one to read VISIM parameter files into a Matlab structure. Any VISIM option can be changed through this structure.
Using mGstat, VISIM can be used to perform Conditional Simulation thorugh Error Simulation.
[..more in the manual]
An interface to SGeMS
SGeMS[www] (the Stanford Geostatistical Modeling Software) can be called interactively from within Matlab. SGeMS provides state of the art geostatistical simulation algorithms, such as multiple-point based SNESIM and FILTERSIM codes, as well as classical 2-point algorithms, such as sequential Gaussian simulation and direct sequential simulation.
[..more in the manual]
(C) 2004-2024 Thomas Mejer Hansen, [mail - www]
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