RandomFields (version 3.1.36)

RFspatialPointsDataFrame-class: Class "RFspatialPointsDataFrame"

Description

Class for spatial attributes that have spatial or spatio-temporal locations (at least of dimension 2) that are not on a grid. Direct extension of class SpatialPointsDataFrame from the sp-package. See sp2RF for an explicite transformation.

Usage

"RFspDataFrame2conventional"(obj)

Arguments

obj

an RFspatialPointsDataFrame object

Creating Objects

Objects can be created by using the functions RFspatialPointsDataFrame or conventional2RFspDataFrame or by calls of the form as(x, "RFspatialPointsDataFrame"), where x is of class RFspatialPointsDataFrame.

Slots

Extends

Class SpatialPointsDataFrame, directly. Class SpatialPoints, by class SpatialPointsDataFrame. Class Spatial, by class SpatialPoints.

Methods

Details

Note that in the data-slot, each colums is ordered according to the ordering of coordinates(grid), the first dimension runs fastest and for all BUT the second dimension, coordinate values are in ascending order. In the second dimension, coordinate values run from high to low. Hence, when converting to conventional formats using RFspDataFrame2conventional or RFspDataFrame2dataArray, the data array is re-ordered such that all dimensions are in ascending order. as.matrix does not perform re-ordering. Methods summary and dimensions are defined for the “parent”-class RFsp.

See Also

RFspatialGridDataFrame-class, which is for point locations that are on a grid, RFpointsDataFrame-class which is for one-dimensional locations, RFsp, sp2RF

Examples

RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again

x <- cbind(runif(50), runif(50))
f <- RFsimulate(model=RMexp(), x=x, n=3)

str(f)
str(RFspDataFrame2conventional(f))
head(coordinates(f))
str(f[2]) ## selects second column of data-slot
all.equal(f, cbind(f,f)[1:3]) ## TRUE
try(as(f, "RFspatialGridDataFrame")) # yields error

plot(f, nmax=2)

f2 <- RFsimulate(model=RMwhittle(nu=1.2, scale=10), x=cbind(x,x), n=4)
plot(f2, MARGIN=c(3,4), nmax=2)

f.sp <- RFsimulate(model=RMexp(), x=x, n=3, seed=0)
f.old <- RFsimulate(model=RMexp(), x=x, n=3, spConform=FALSE, seed=0)
all.equal(RFspDataFrame2conventional(f.sp)$data, f.old) ## TRUE