fields

A collection of programs written in the R language for curve and function fitting with an emphasis on spatial data.

Authors/Contributors and Citation

Fields has drawn heavily from its predecessor, FUNFITS, to the extent that it is hard to separate who is primarily responsible for what. With that in mind, giving credit to everyone involved in FUNFITS and Fields seems appropriate. In no particular order, the Fields Development Team is: Doug Nychka, Reinhard Furrer, Steve Sain, Barbara Bailey, Stephen Ellner, Perry Haaland, Michael O'Connell, Sarah Hardy, Jungmin Baik, Wendy Meiring, J. Andrew Royle, Montserrat Fuentes, Tim Hoar, Claudia Tebaldi, and Eric Gilleland.

Citing fields
Fields Development Team (2006). fields: Tools for Spatial Data. National Center for Atmospheric Research, Boulder, CO. URL http://www.cgd.ucar.edu/Software/Fields.

Availability

The R version of Fields is currently available for UNIX, Linux and Windows through the Comprehensive R Archive Network (CRAN). [See the contributed packages section]. The Windows version is available as a binary, the others can be readily built in UNIX/LINUX. Currently, due to time constraints, we no longer offer fields for Splus.

A development version

fields_3.5.1.tar.gz (posted 19-JUN-2007) This may be slightly different than the version available from CRAN and not checked completely.

The major methods implemented as R/S functions include:

• Tps: Thin Plate spline regression
• Krig: Spatial process estimate (Kriging)
  krig.image: Spatial process estimate for large problems.
  All Kriging functions allow you to supply a covariance function that is written in R code.
• cover.design: Finds a space filling design
• as.image, image.plot, smooth.image, quilt.plot, drape.plot: Some useful functions for working with data on 2-d grids.
• sreg, qsreg : 1-d smoothing splines and 1-d quantile splines

There are also generic functions that support these methods such as

• plot diagnostic plots of fit
• summary- statistical summary of fit
• print- shorter version of summary
• surface- graphical display of fitted surface
• predict- evaluation fit at arbitrary points
• predict.se- prediction standard errors at arbitrary points.
• sim.Krig Conditional simulation of the spatial field given the observations

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For problems with the page, contact Tim Hoar - thoar 'at' ucar 'dot' edu

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