svar.bin {npsp}

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.