R: Reorganisation of cokriged compositions

gsi.gstatCokriging2compo {gmGeostats}

R Documentation

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)