gsi.gstatCokriging2compo: Reorganisation of cokriged compositions

In gmGeostats: Geostatistics for Compositional Analysis

Reorganisation of cokriged compositions

Description

Produce compositional predictions out of a gstat::gstat() prediction

Usage

gsi.gstatCokriging2compo(COKresult, ...)

## Default S3 method:
gsi.gstatCokriging2compo(COKresult, ...)

## S3 method for class 'data.frame'
gsi.gstatCokriging2compo(
  COKresult,
  V = NULL,
  orignames = NULL,
  tol = 1e-12,
  nscore = FALSE,
  gg = NULL,
  ...
)

## Default S3 method:
gsi.gstatCokriging2rmult(COKresult, ...)

## S3 method for class 'data.frame'
gsi.gstatCokriging2rmult(COKresult, nscore = FALSE, gg = NULL, ...)

Arguments

COKresult	output of a gstat::predict.gstat() cokriging, typically of class "data.frame", sp::SpatialPointsDataFrame(), sp::SpatialGridDataFrame() or sp::SpatialPixelsDataFrame()
...	further arguments needed for nscore (deprecated)
V	string or matrix describing which logratio was applied ("ilr", "alr", or a matrix computing the ilr corrdinates; clr is not allowed!)
orignames	names of the original components (optional, but recommended)
tol	for generalized inversion of the matrix (rarely touched!)
nscore	boolean, were the data normal score-transformed? (deprecated)
gg	in the case that normal score transformation was applied, provide the gstat object! (deprecated)

Value

an (N,D)-object of class c("spatialGridAcomp","acomp") with the predictions, together with an extra attribute "krigVar" containing the cokriging covariance matrices in an (N, D, D)-array; here N=number of interpolated locations, D=number of original components of the composition

Methods (by class)

• default: Reorganisation of cokriged compositions

• data.frame: Reorganisation of cokriged compositions

• default: Reorganisation of cokriged multivariate data

• data.frame: Reorganisation of cokriged multivariate data

See Also

image_cokriged.spatialGridRmult() for an example

gmGeostats documentation built on April 18, 2023, 5:08 p.m.