Description
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 supporting by functions that can determine the
smoothing parameter (nugget and sill variance) by cross validation
and also by restricted maximum likelihood. For Kriging there is
an easy to 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 and
currently requires the sparse matrix (spam) package.
Use help(fields) to get started and for an
overview. The fields source code is deliberately commented and
provides useful explanations of numerical details in addition to the
manual pages. The commented source code can be viewed by expanding the
source code .tar.gz file and looking in R subdirectory.