# fields v11.6

Monthly downloads

## 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 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.

## Functions in fields

Name | Description | |

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. | |

Krig.Amatrix | Smoother (or "hat") matrix relating predicted values to the dependent (Y) values. | |

CovarianceUpper | Evaluate covariance over upper triangle of distance matrix | |

Colorado Monthly Meteorological Data | Monthly surface meterology for Colorado 1895-1997 | |

fields exported FORTRAN | FORTRAN subroutines used in fields functions | |

The Engines: | Basic linear algebra utilities and other computations supporting the Krig function. | |

Exponential, Matern, Radial Basis | Covariance functions | |

Krig.null.function | Default function to create fixed matrix part of spatial process model. | |

CO2 | Simulated global CO2 observations | |

Krig | Kriging surface estimate | |

NorthAmericanRainfall | Observed North American summer precipitation from the historical climate network. | |

add.image | Adds an image to an existing plot. | |

RMprecip | Monthly total precipitation (mm) for August 1997 in the Rocky Mountain Region and some gridded 4km elevation data sets (m). | |

Tps | Thin plate spline regression | |

compactToMat | Convert Matrix from Compact Vector to Standard Form | |

drape.plot | Perspective plot draped with colors in the facets. | |

colorbar.plot | Adds color scale strips to an existing plot. | |

US.dat | Outline of coterminous US and states. | |

US | Plot of the US with state boundaries | |

cover.design | Computes Space-Filling "Coverage" designs using Swapping Algorithm | |

RCMexample | 3-hour precipitation fields from a regional climate model | |

arrow.plot | Adds arrows to a plot | |

as.surface | Creates an "surface" object from grid values. | |

as.image | Creates image from irregular x,y,z | |

QTps | Robust and Quantile smoothing using a thin-plate spline | |

Krig.replicates | Collapse repeated spatial locations into unique locations | |

image.cov | Exponential, Matern and general covariance functions for 2-d gridded locations. | |

REML.test | Maximum Likelihood estimates for some Matern covariance parameters. | |

rat.diet | Experiment studying an appetite supressant in rats. | |

grid list | Some simple functions for working with gridded data and the grid format (grid.list) used in fields. | |

quilt.plot | Image plot for irregular spatial data. | |

ozone2 | Daily 8-hour ozone averages for sites in the Midwest | |

MLESpatialProcess | Estimates key covariance parameters for a spatial process. | |

plot.Krig | Diagnostic and summary plots of a Kriging, spatialProcess or spline object. | |

fields internal | Fields internal and secondary functions | |

Wendland | Wendland family of covariance functions and supporting numerical functions | |

WorldBankCO2 | Carbon emissions and demographic covariables by country for 1999. | |

set.panel | Specify a panel of plots | |

sim.spatialProcess | Conditional simulation of a spatial process | |

envelopePlot | Add a shaded the region between two functions to an existing plot | |

bplot | boxplot | |

fields.hints | fields - graphics hints | |

bplot.xy | Boxplots for conditional distribution | |

fields | fields - tools for spatial data | |

interp.surface | Fast bilinear interpolator from a grid. | |

lennon | Gray image of John Lennon. | |

image2lz | Some simple functions for subsetting images | |

fields testing scripts | Testing fields functions | |

Covariance functions | Exponential family, radial basis functions,cubic spline, compactly supported Wendland family and stationary covariances. | |

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. | |

fields.grid | Using MKrig for predicting on a grid. | |

predictSurface | Evaluates a fitted function or the prediction error as a surface that is suitable for plotting with the image, persp, or contour functions. | |

minitri | Mini triathlon results | |

Chicago ozone test data | Data set of ozone measurements at 20 Chicago monitoring stations. | |

predict.Krig | Evaluation of Krig spatial process estimate. | |

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. | |

predictSE | Standard errors of predictions for Krig spatial process estimate | |

registeringCode | Information objects that register C and FORTRAN functions. | |

splint | Cubic spline interpolation | |

print.Krig | Print kriging fit results. | |

world | Plot of the world | |

sreg | Cubic smoothing spline regression | |

fields-stuff | Fields supporting functions | |

xline | Draw a vertical line | |

yline | Draw horizontal lines | |

flame | Response surface experiment ionizing a reagent | |

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. | |

image.smooth | Kernel smoother for irregular 2-d data | |

stats | Calculate summary statistics | |

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. | |

stats.bin | Bins data and finds some summary statistics. | |

mKrig | "micro Krig" Spatial process estimate of a curve or surface, "kriging" with a known covariance function. | |

pushpin | Adds a "push pin" to an existing 3-d plot | |

qsreg | Quantile or Robust spline regression | |

poly.image | Image plot for cells that are irregular quadrilaterals. | |

plot.surface | Plots a surface | |

summary.ncdf | Summarizes a netCDF file handle | |

summary.Krig | Summary for Krig or spatialProcess estimated models. | |

circulantEmbedding | Efficiently Simulates a Stationary 1 and 2D Gaussian random fields | |

supportsArg | Tests if function supports a given argument | |

surface.Krig | Plots a surface and contours | |

rdist.earth | Great circle distance matrix or vector | |

rdist | Euclidean distance matrix or vector | |

transformx | Linear transformation | |

smooth.2d | Kernel smoother for irregular 2-d data | |

tim.colors | Some useful color tables for images and tools to handle them. | |

spam2lz | Conversion of formats for sparse matrices | |

vgram | Traditional or robust variogram methods for spatial data | |

spatialProcess | Estimates a spatial process model. | |

vgram.matrix | Computes a variogram from an image | |

No Results! |

## Last month downloads

## Details

Date | 2020-10-06 |

License | GPL (>= 2) |

URL | https://github.com/NCAR/Fields |

NeedsCompilation | yes |

Repository | CRAN |

Packaged | 2020-10-06 18:52:30 UTC; nychka |

Date/Publication | 2020-10-09 10:50:07 UTC |

imports | maps |

depends | methods , R (>= 3.0) , spam |

Contributors | , Douglas Nychka, Reinhard Furrer, John Paige, Stephan Sain, Matthew Iverson |

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