GNU R tools for spatial data
For curve, surface and function fitting with an emphasis on splines,
spatial data and spatial statistics. The major methods include cubic,
and thin plate splines, Kriging and compact covariances for large data
sets. The splines and Kriging methods are supported by functions that
can determine the smoothing parameter (nugget and sill variance) and
other covariance parameters by cross validation and also by restricted
maximum likelihood. For Kriging there is an easy to use function that
also estimates the correlation scale (range). A major feature is that
any covariance function implemented in R and following a simple fields
format can be used for spatial prediction. There are also many useful
functions for plotting and working with spatial data as images. This
package also contains an implementation of sparse matrix methods for
large spatial data sets.
