Tools for Spatial Data
Adds an image to an existing plot.
Adds arrows to a plot
Creates image from irregular x,y,z
Creates an "surface" object from grid values.
Data frame of the effect of buffer compositions on DNA strand displace...
boxplot
Boxplots for conditional distribution
Monthly surface meterology for Colorado 1895-1997
Adds color scale strips to an existing plot.
Convert Matrix from Compact Vector to Standard Form
Evaluate covariance over upper triangle of distance matrix
Computes Space-Filling "Coverage" designs using Swapping Algorithm
Perspective plot draped with colors in the facets.
Add a shaded the region between two functions to an existing plot
Exponential family, radial basis functions,cubic spline, compactly sup...
Covariance functions
Fields internal and secondary functions
Fields supporting functions
Using MKrig for predicting on a grid.
fields - graphics hints
fields - tools for spatial data
Testing fields functions
Response surface experiment ionizing a reagent
FORTRAN subroutines used in fields functions
Some simple functions for working with gridded data and the grid forma...
Exponential, Matern and general covariance functions for 2-d gridded l...
Draws an image plot with a legend strip for the color scale based on e...
Kernel smoother for irregular 2-d data
Some simple functions for subsetting images
Draws an image plot with a legend strip for the color scale based on e...
Fast bilinear interpolator from a grid.
Smoother (or "hat") matrix relating predicted values to the dependent ...
Basic linear algebra utilities and other computations supporting the K...
Default function to create fixed matrix part of spatial process model.
Kriging surface estimate
Collapse repeated spatial locations into unique locations
Finds profile likelihood and GCV estimates of smoothing parameters for...
Mini triathlon results
"micro Krig" Spatial process estimate of a curve or surface, "kriging"...
Maximizes likelihood for the process marginal variance (sigma) and nug...
Utilities for fast spatial prediction.
Data set of ozone measurements at 20 Chicago monitoring stations.
Diagnostic and summary plots of a Kriging, spatialProcess or spline ob...
Plots a surface
Image plot for cells that are irregular quadrilaterals.
Evaluation of Krig spatial process estimate.
Standard errors of predictions for Krig spatial process estimate
Evaluates a fitted function or the prediction error as a surface that ...
Print kriging fit results.
Adds a "push pin" to an existing 3-d plot
Quantile or Robust spline regression
Robust and Quantile smoothing using a thin-plate spline
Useful plots for visualizing irregular spatial data.
Great circle distance matrix or vector
Euclidean distance matrix or vector
Information objects that register C and FORTRAN functions.
Adds to an existing plot, a ribbon of color, based on values from a co...
Monthly total precipitation (mm) for August 1997 in the Rocky Mountain...
Specify a panel of plots
Unconditional and conditional simulation of a spatial process
Efficiently Simulates a Stationary 1 and 2D Gaussian random fields
Kernel smoother for irregular 2-d data
Conversion of formats for sparse matrices
Estimates a spatial process model.
Cubic spline interpolation
Cubic smoothing spline regression
Bins data and finds some summary statistics.
Calculate summary statistics
Summary for Krig or spatialProcess estimated models.
Summarizes a netCDF file handle
Tests if function supports a given argument
Plots a surface and contours
Some useful color tables for images and tools to handle them.
Thin plate spline regression
Linear transformation
Plot of the US with state boundaries
Computes a variogram from an image
Traditional or robust variogram methods for spatial data
Wendland family of covariance functions and supporting numerical funct...
Plot of the world
Carbon emissions and demographic covariables by country for 1999.
Draw a vertical line
Draw horizontal lines
For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding the source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857, the National Center for Atmospheric Research, and Colorado School of Mines. See the Fields URL for a vignette on using this package and some background on spatial statistics.