fields v10.3

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Tools for Spatial Data

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 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 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.

Functions in fields

Name Description
fields exported FORTRAN FORTRAN subroutines used in fields functions
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.
Colorado Monthly Meteorological Data Monthly surface meterology for Colorado 1895-1997
CO2 Simulated global CO2 observations
CovarianceUpper Evaluate covariance over upper triangle of distance matrix
Exponential, Matern, Radial Basis Covariance functions
Krig.Amatrix Smoother (or "hat") matrix relating predicted values to the dependent (Y) values.
Krig.null.function Default function to create fixed matrix part of spatial process model.
The Engines: Basic linear algebra utilities and other computations supporting the Krig function.
Krig Kriging surface estimate
RCMexample 3-hour precipitation fields from a regional climate model
RMprecip Monthly total precipitation (mm) for August 1997 in the Rocky Mountain Region and some gridded 4km elevation data sets (m).
Krig.replicates Collapse repeated spatial locations into unique locations
NorthAmericanRainfall Observed North American summer precipitation from the historical climate network.
QTps Robust and Quantile smoothing using a thin-plate spline
MLESpatialProcess Estimates key covariance parameters for a spatial process.
colorbar.plot Adds color scale strips to an existing plot.
arrow.plot Adds arrows to a plot
add.image Adds an image to an existing plot.
REML.test Maximum Likelihood estimates for some Matern covariance parameters.
compactToMat Convert Matrix from Compact Vector to Standard Form
WorldBankCO2 Carbon emissions and demographic covariables by country for 1999.
fields.hints fields - graphics hints
lennon Gray image of John Lennon.
fields testing scripts Testing fields functions
fields internal Fields internal and secondary functions
US.dat Outline of coterminous US and states.
mKrig.MLE Maximizes likelihood for the process marginal variance (rho) and nugget standard deviation (sigma) parameters (e.g. lambda) over a many covariance models or covariance parameter values.
bplot boxplot
drape.plot Perspective plot draped with colors in the facets.
fields.grid Using MKrig for predicting on a grid.
fields fields - tools for spatial data
ozone2 Daily 8-hour ozone averages for sites in the Midwest
bplot.xy Boxplots for conditional distribution
as.image Creates image from irregular x,y,z
plot.Krig Diagnostic and summary plots of a Kriging, spatialProcess or spline object.
image2lz Some simple functions for subsetting images
Tps Thin plate spline regression
fields-stuff Fields supporting functions
image.cov Exponential, Matern and general covariance functions for 2-d gridded locations.
US Plot of the US with state boundaries
flame Response surface experiment ionizing a reagent
grid list Some simple functions for working with gridded data and the grid format (grid.list) used in fields.
predict.Krig Evaluation of Krig spatial process estimate.
Wendland Wendland family of covariance functions and supporting numerical functions
predictSE Standard errors of predictions for Krig spatial process estimate
cover.design Computes Space-Filling "Coverage" designs using Swapping Algorithm
interp.surface Fast bilinear interpolator from a grid.
gcv.Krig Finds profile likelihood and GCV estimates of smoothing parameters for splines and Kriging.
ribbon.plot Adds to an existing plot, a ribbon of color, based on values from a color scale, along a sequence of line segments.
minitri Mini triathlon results
registeringCode Information objects that register C and FORTRAN functions.
Chicago ozone test data Data set of ozone measurements at 20 Chicago monitoring stations.
summary.Krig Summary for Krig or spatialProcess estimated models.
summary.ncdf Summarizes a netCDF file handle
envelopePlot Add a shaded the region between two functions to an existing plot
spam2lz Conversion of formats for sparse matrices
spatialProcess Estimates a spatial process model.
Covariance functions Exponential family, radial basis functions,cubic spline, compactly supported Wendland family and stationary covariances.
as.surface Creates an "surface" object from grid values.
image.plot Draws an image plot with a legend strip for the color scale based on either a regular grid or a grid of quadrilaterals.
plot.surface Plots a surface
image.smooth Kernel smoother for irregular 2-d data
mKrig "micro Krig" Spatial process estimate of a curve or surface, "kriging" with a known covariance function.
sim.rf Simulates a Stationary Gaussian random field
poly.image Image plot for cells that are irregular quadrilaterals.
print.Krig Print kriging fit results.
predictSurface Evaluates a fitted function or the prediction error as a surface that is suitable for plotting with the image, persp, or contour functions.
splint Cubic spline interpolation
qsreg Quantile or Robust spline regression
pushpin Adds a "push pin" to an existing 3-d plot
mKrigMLE Maximizes likelihood for the process marginal variance (rho) and nugget standard deviation (sigma) parameters (e.g. lambda) over a many covariance models or covariance parameter values.
xline Draw a vertical line
vgram Traditional or robust variogram methods for spatial data
sreg Cubic smoothing spline regression
sim.spatialProcess Conditional simulation of a spatial process
rdist Euclidean distance matrix or vector
rat.diet Experiment studying an appetite supressant in rats.
quilt.plot Image plot for irregular spatial data.
smooth.2d Kernel smoother for irregular 2-d data
world Plot of the world
vgram.matrix Computes a variogram from an image
set.panel Specify a panel of plots
yline Draw horizontal lines
rdist.earth Great circle distance matrix or vector
stats Calculate summary statistics
stats.bin Bins data and finds some summary statistics.
supportsArg Tests if function supports a given argument
tim.colors Some useful color tables for images and tools to handle them.
transformx Linear transformation
surface.Krig Plots a surface and contours
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Details

Date 2020-03-02
License GPL (>= 2)
URL https://github.com/NCAR/Fields
NeedsCompilation yes
Packaged 2020-02-03 18:13:15 UTC; nychka
Repository CRAN
Date/Publication 2020-02-04 16:30:02 UTC

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