svar.bin: Linear binning of semivariances

In npsp: Nonparametric Spatial Statistics

Linear binning of semivariances

Description

Creates a svar.bin (binned semivar. + grid parameters) object with linearly binned semivariances (i.e. computes a binned sample variogram).

Usage

svar.bin(x, ...)

## Default S3 method:
svar.bin(
  x,
  y,
  maxlag = NULL,
  nlags = NULL,
  minlag = maxlag/nlags,
  estimator = c("classical", "modulus"),
  ...
)

svariso(
  x,
  y,
  maxlag = NULL,
  nlags = NULL,
  minlag = maxlag/nlags,
  estimator = c("classical", "modulus"),
  ...
)

Arguments

x	object used to select a method. Usually a matrix with the coordinates of the data locations (columns correspond with dimensions and rows with data).
...	further arguments passed to or from other methods.
y	vector of data (response variable).
maxlag	maximum lag. Defaults to 55% of largest lag.
nlags	number of lags. Defaults to max(12, rule.svar(x)).
minlag	minimun lag.
estimator	character, estimator name (e.g. "classical"). See "Details" below.

Details

Currently, only isotropic semivariogram estimation is supported.

If parameter nlags is not specified is set to max(12, rule.svar(x)).

Value

Returns an S3 object of class svar.bin (extends bin.data), a data.grid object with the following 4 components:

biny	array (dimension nlags) with the binned semivariances.
binw	array (dimension nlags) with the bin counts (weights).
grid	a grid.par-class object with the grid parameters.
data	a list with 3 components: x argument x. y argument y. med (weighted) mean of the (binned) semivariances.
svar	a list of 2 components: type character, type of estimation (e.g. "isotropic"). estimator character, estimator name (e.g. "classical").

See Also

np.svariso, np.svar, data.grid, binning, locpol, rule.svar.

npsp documentation built on May 4, 2023, 1:07 a.m.