create a semivariogram matrix between a set of locations, or semivariogram matrices between and within two sets of locations

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Description

varMat will create a semivariogram matrix between all the supports in a set of locations (observations or prediction locations) or semivariogram matrices between all the supports in one or two sets of locations, and also between them.

Usage

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## S3 method for class 'rtop'
varMat(object, varMatUpdate = FALSE, fullPred = FALSE, params = list(), ...) 
## S3 method for class 'SpatialPolygonsDataFrame'
varMat(object, object2 = NULL,...) 
## S3 method for class 'SpatialPolygons'
varMat(object, object2 = NULL, variogramModel,
     overlapObs, overlapPredObs, ...) 

## S3 method for class 'list'
varMat(object, object2 = NULL, coor1, coor2, maxdist = Inf, 
              variogramModel, diag = FALSE, sub1, sub2, 
              debug.level = 1, ...) 

Arguments

object

either: 1) an object of class rtop (see rtop-package) or 2) a
SpatialPolygonsDataFrame, or SpatialPolygons, or 3) a
matrix with geostatistical distances (see gDist or 4) a list with discretized supports

varMatUpdate

logical; if TRUE, also existing variance matrices will be recomputed, if FALSE, only missing variance matrices will be computed

fullPred

logical; whether to create the full covariance matrix also for the predictions, mainly used for simulations

params

a set of parameters, used to modify the standard parameters for the rtop package, set in getRtopParams.

object2

if object is not an object of class rtop; an object of the same class as object with a possible second set of locations with support

variogramModel

variogramModel to be used in calculation of the semivariogram matrix (matrices)

...

typical parameters to modify from the default parameters of the rtop-package (or modifications of the previously set parameters for the rtop-object), see also getRtopParams. These can also be passed in a list named params, as for the rtop-method. Typical parameters to modify for this function:

  • rresol = 100miminum number of discretization points, in call to rtopDisc if necessary

  • rstype = "rtop"sampling type from areas, in call to rtopDisc if necessary

  • gDistPred = FALSEuse geostatistical distance for semivariogram matrices

  • gDistparameter to set jointly gDistEst = gDistPred = gDist

overlapObs

matrix with observations that overlap each other

overlapPredObs

matrix with observations and predictionLocations that overlap each other

coor1

coordinates of centroids of object

coor2

coordinates of centre-of-gravity of object2

maxdist

maximum distance between areas for inclusion in semivariogrma matrix

diag

logical; if TRUE only the semivariogram values along the diagonal will be calculated, typical for semivariogram matrix of prediction locations

sub1

semivariogram array for subtraction of inner variances of areas

sub2

semivariogram array for subtraction of inner variances of areas

debug.level

debug.level >= 1 will give output for every element

Value

The lower level versions of the function calculates a semivariogram matrix between locations in object or between the locations in object and the locations in object2. The method for object of type rtop calculates semivariogram matrices between observation locations, between prediction locations, and between observation locations and prediction locations, and adds these to object.

Note

The argument varMatUpdate is typically used to avoid repeated computations of the same variance matrices. Default is FALSE, which will avoid recomputation of the variance matrix for the observations if the procedure is cross-validation before interpolation. Should be set to TRUE if the variogram Model has been changed, or if observation and/or prediction locations have been changed.

If an rtop-object contains observations and/or predictionLocations of type STSDF, the covariance matrix is computed based on the spatial properties of the object.

Author(s)

Jon Olav Skoien

See Also

gDist, rtop-package

Examples

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## Not run: 
library(rgdal)
rpath = system.file("extdata",package="rtop")
observations = readOGR(rpath,"observations")
gDist = gDist(observations)
vmod = list(model = "Ex1", params = c(0.00001,0.007,350000,0.9,1000))
vm = varMat(gDist$gDistObs, variogramModel = vmod)

## End(Not run)