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fields (version 1.0)

Tools for spatial data

Description

FIELDS is a collection of programs for curve and function fitting with an emphasis on spatial data. The major methods implemented include cubic and thin plate splines, universal Kriging and Kriging for large data sets. The main feature is that any covariance function implemented in R can be used for spatial prediction.

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Version

Install

install.packages('fields')

Monthly Downloads

46,589

Version

1.0

License

GPL Version 2 or later.

Maintainer

Douglas Nychka

Last Published

October 1st, 2024

Functions in fields (1.0)

as.surface

Creates an "surface" object from grid values.
image.plot

Draws image plot with a legend strip for the color scale.
arrow.plot

Adds arrows to a plot
grid list

Grid list for describing equally spaced grids
smooth.2d

Kernel smoother for irregular 2-d data
cover.design

Computes Space-Filling "Coverage" designs using Swapping Algorithm
Wtransform.sim

Simulates a 2-d random wavelet field
predict.surface

Evaluates a fitted function as a surface object
US

Plot of the US with state boundaries
print.Krig

Print kriging fit results.
stats.bin

Bins data and finds some summary statistics.
make.Amatrix.krig

Computes the prediction matrix for a Krig fit.
sreg

Smoothing spline regression
image.count

Creates image for a 2-d histogram from irregular locations
matern.cov

Matern covariance function
Krig

Kriging surface estimate
poisson.cov

Poisson spherical covariance function
fields internal

Fields internal and secondary functions
exp.image.cov

Exponential,Gaussian and "power" covariance family for 2-d gridded locations
predict.se

Standard errors of predictions
Tps

Thin plate spline regression
image.smooth

Kernel smoother for irregular 2-d data
BD

Data frame of the effect of buffer compositions on DNA strand displacement amplification. A 4-d regression data set with with replication. This is a useful test data set for exercising function fitting methods.
flame

Response surface experiment ionizing a reagent
plot.surface

Plots a surface
predict.Krig

Evaluation of Krig spatial process estimate.
vgram.matrix

Computes a variogram from an image
ozone2

Daily 8-hour ozone averages for sites in the Midwest
xline

Draw a vertical line
world

Plot of the world
krig.image

Spatial process estimate for large irregular 2-d dats sets.
bplot

boxplot
surface.Krig

Plots a surface and contours
predict.se.Krig

Standard errors of predictions for Krig spatial process estimate
yline

Draw horizontal lines
ozone

Data set of ozone measurements at 20 Chicago monitoring stations.
set.panel

Specify a panel of plots
qsreg

Quantile spline regression
nkreg

Normal kernel regression estimate
rdist.earth

Great circle distance matrix
summary.krig

Summary for Krig spatial process estimate
vgram

Finds a traditional or robust variogram for spatial data.
plot.Krig

Diagnostic and summary plots of the Krig object
precip

Standardized monthly precipitation for August 1963 inteh Rocky Mountain Region
bplot.xy

Boxplots for conditional distribution
predict.surface.se

Standard errors of predictions
splint

Cubic spline interpolation
exp.cov

Exponential, Gaussian and "power" covariance family
rdist

Euclidean distance matrix
stats

Calculate summary statistics
make.Amatrix

Matrix relating predicted values to the dependent (Y) values
minitri

Mini triathlon results
Wtransform.image

Quadratic W wavelet transform for an image
sim.rf

Simulates a random field
lennon

Gray image of John Lennon.
interp.surface

Fast bilinear interpolator from a grid.
as.image

Creates image from irregular x,y,z
plot.sreg

Plots smoothing spline regression object
transformx

Linear transformation
rat.diet

Experiment studying an appetite supressant in rats.