Package index • gstat

All functions

DE_RB_2005: Spatio-temporal data set with rural background PM10 concentrations in Germany 2005

coalash: Coal ash samples from a mine in Pennsylvania

estiStAni(): Estimation of the spatio-temporal anisotropy

extractPar() extractParNames(): Extracting parameters and their names from a spatio-temporal variogram model

fit.StVariogram(): Fit a spatio-temporal sample variogram to a sample variogram

fit.lmc(): Fit a Linear Model of Coregionalization to a Multivariable Sample Variogram

fit.variogram(): Fit a Variogram Model to a Sample Variogram

fit.variogram.gls(): GLS fitting of variogram parameters

fit.variogram.reml(): REML Fit Direct Variogram Partial Sills to Data

fulmar: Fulmaris glacialis data

get.contr(): Calculate contrasts from multivariable predictions

gstat() print(<gstat>): Create gstat objects, or subset it

hscat(): Produce h-scatterplot

image(<data.frame>) xyz2img(): Image Gridded Coordinates in Data Frame

jura: Jura data set

krige() krige.locations() krige.spatial() krige0() idw() idw.locations() idw.spatial() idw0(): Simple, Ordinary or Universal, global or local, Point or Block Kriging, or simulation.

gstat.cv() krige.cv() krige.cv.locations() krige.cv.spatial(): (co)kriging cross validation, n-fold or leave-one-out

krigeST() krigeSTTg(): Ordinary global Spatio-Temporal Kriging

krigeSTSimTB(): conditional/unconditional spatio-temporal simulation

krigeSimCE(): Simulation based on circulant embedding

krigeTg(): TransGaussian kriging using Box-Cox transforms

map.to.lev(): rearrange data frame for plotting with levelplot

meuse.all: Meuse river data set – original, full data set

meuse.alt: Meuse river altitude data set

ncp.grid: Grid for the NCP, the Dutch part of the North Sea

ossfim(): Kriging standard errors as function of grid spacing and block size

oxford: Oxford soil samples

pcb: PCB138 measurements in sediment at the NCP, the Dutch part of the North Sea

plot(<gstatVariogram>) plot(<variogramMap>) plot(<StVariogram>): Plot a sample variogram, and possibly a fitted model

plot(<pointPairs>): Plot a point pairs, identified from a variogram cloud

plot(<variogramCloud>): Plot and Identify Data Pairs on Sample Variogram Cloud

predict(<gstat>): Multivariable Geostatistical Prediction and Simulation

get_gstat_progress() set_gstat_progress(): Get or set progress indicator

show.vgms(): Plot Variogram Model Functions

sic2004: Spatial Interpolation Comparison 2004 data set: Natural Ambient Radioactivity

sic97: Spatial Interpolation Comparison 1997 data set: Swiss Rainfall

spplot.vcov(): Plot map matrix of prediction error variances and covariances

tull: Südliche Tullnerfeld data set

variogram(<gstat>) variogram(<formula>) variogram(<default>) print(<gstatVariogram>) print(<variogramCloud>): Calculate Sample or Residual Variogram or Variogram Cloud

variogramLine(): Semivariance Values For a Given Variogram Model

variogramST(): Calculate Spatio-Temporal Sample Variogram

variogramSurface(): Semivariance values for a given spatio-temporal variogram model

vgm() print(<variogramModel>) plot(<variogramModel>) as.vgm.variomodel(): Generate, or Add to Variogram Model

vgm.panel.xyplot() panel.pointPairs(): panel functions for most of the variogram plots through lattice

vgmArea(): point-point, point-area or area-area semivariance

vgmAreaST(): Function that returns the covariances for areas

vgmST(): Constructing a spatio-temporal variogram

vv: Precomputed variogram for PM10 in data set air

walker: Walker Lake sample and exhaustive data sets

wind: Ireland wind data, 1961-1978