Gstat is a program for the modelling, prediction and simulation of
geostatistical data in one, two or three dimensions.  Geostatistical
data are data (measurements) collected at known locations in space,
from a function (process) that has a value at every location in a
certain (1, 2 or 3-D) domain. These data (or some transform of them)
are modelled as the sum of a constant or varying trend and a spatially
correlated residual. Given a model for the trend, and under some
stationarity assumptions, geostatistical modelling involves the
estimation of the spatial correlation. Geostatistical prediction
(`kriging') is finding the best linear unbiased prediction (the
expected value) with its prediction error for a variable at a
location, given observations and a model for their spatial
variation. Simulation of a spatial variable is the creation of
randomly drawn realizations of a field given a model for the data,
possibly conditioned on observations.