# fields: Tools for Spatial Data doi:10.5065/D6W957CT

## The fields package

To browse the help files: index

To browse source code with the comments retained: fields source directory

For the most recent version of fields please use the R studio CRAN mirror to download and install fields. Use citation("fields") in R to generate a citation with the current version number and this doi.

## Standard R package description:

Package: fields
Version: 8.4-1
Date: 2016-05-03
Title: Tools for Spatial Data
Authors@R: c( person("Douglas", "Nychka", role = c("aut", "cre"),
email = "nychka@ucar.edu"),
person("Reinhard", "Furrer", role = c("aut"),
email = "reinhard.furrer@math.uzh.ch"),
person("John", "Paige", role = c("aut"),
email = "paigejo@uw.edu"),
person("Stephan", "Sain", role = "aut",
email = "ssain@ucar.edu"))
Author: Douglas Nychka [aut, cre], Reinhard Furrer [aut], John Paige [aut], Step
han Sain [aut]
Maintainer: Douglas Nychka <nychka@ucar.edu>
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
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 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 file (ending in tar.gz)
and looking in the R subdirectory. Please cite fields along with its
URL: http://www.image.ucar.edu/fields
Depends: R (>= 3.0), methods, spam, maps
NeedsCompilation: yes
Packaged: 2016-05-03 21:42:53 UTC; nychka