Local polinomial estimation

Nonparametric estimation of a multidimensional regression function (e.g. a spatial trend), a probability density function or a semivariogram. To speed up computations, linear binning is used to discretize the (corresponding) data. A full bandwidth matrix and a multiplicative triweight kernel is used to compute the weights. Main calculations are performed in FORTRAN using the LAPACK library.

npsp-package

npsp: Nonparametric spatial (geo)statistics

np.fitgeo()

Fit a nonparametric geostatistical model

locpol() locpolhcv()

Local polynomial estimation

np.den()

Local polynomial density estimation

np.svar() np.svariso() np.svariso.hcv() np.svariso.corr()

Local polynomial estimation of the semivariogram

interp() predict(<locpol.bin>) predict(<np.den>)

Fast linear interpolation of a regular grid

np.geo()

Nonparametric geostatistical model (S3 class "np.geo")

Bandwidth selection

Cross-validation methods for bandwidth selection in local polynomial kernel smoothing.

h.cv() hcv.data()

Cross-validation methods for bandwidth selection

Linear binning

Methods for multidimensional linear binning.

binning() as.bin.data()

Linear binning

bin.den() as.bin.den()

Linear binning for density estimation

svar.bin() svariso()

Linear binning of semivariances

Variogram fitting

Flexible (isotropic) Shapiro-Botha variogram model fitting by WLS.

fitsvar.sb.iso()

Fit an isotropic Shapiro-Botha variogram model

disc.sb()

Discretization nodes of a Shapiro-Botha variogram model

Variogram and covariogram utilities

Variogram models and methods.

sv()

Evaluate a semivariogram model

covar()

Covariance values

varcov()

Covariance matrix

svarmod() svarmod.sb.iso() svarmodels()

Define a (semi)variogram model

kappasb()

Coefficients of an extended Shapiro-Botha variogram model

svar.grid()

Discretize a (semi)variogram model

Kriging

Nonparametric residual kriging (sometimes called external drift kriging) and simple kriging.

np.kriging() kriging.simple() kriging.simple.solve()

Nonparametric (residual) kriging

Gridded data

S3 class data.grid and methods.

data.grid()

Gridded data (S3 class "data.grid")

grid.par()

Grid parameters (S3 class "grid.par")

coords()

(spatial) coordinates

coordvalues()

Coordinate values

as.data.grid() as.data.frame(<data.grid>)

data.grid-class methods

interp() predict(<locpol.bin>) predict(<np.den>)

Fast linear interpolation of a regular grid

Plot

Utilities for plotting data with a continuous color scale and other plot methods.

scattersplot()

Exploratory scatter plots

splot() scolor() jet.colors() hot.colors()

Utilities for plotting with a color scale

spoints()

Scatter plot with a color scale

simage() plot(<np.den>)

Image plot with a color scale

spersp()

Perspective plot with a color scale

plot(<fitgeo>)

Plot a nonparametric geostatistical model

plot(<fitsvar>) plot(<svar.bin>) plot(<np.svar>)

Plot a semivariogram object

image(<data.grid>) persp(<data.grid>) contour(<data.grid>)

R Graphics for gridded data

Data sets

Data sets included in the package.

aquifer

Wolfcamp aquifer data

earthquakes

Earthquake data

precipitation

Precipitation data

Other packages

Utilities to interact with other packages.

as.sp()

Convert npsp object to sp object

as.variogram() as.variomodel()

Interface to package "geoR"

as.vgm() vgm.tab.svarmod()

Interface to package "gstat"

Utilities

Other utilities…

mask()

Mask methods

npsp.tolerance()

npsp Tolerances

rule() rule.binning() rule.svar()

npsp Rules

cpu.time()

Total and partial CPU time used