RMcovariate: Model for covariates
In RandomFields: Simulation and Analysis of Random Fields

Description Usage Arguments Details Value Note See Also Examples

The model makes covariates available.

1 2	RMcovariate(formula=NULL, data, x, y=NULL, z=NULL, T=NULL, grid, raw, norm, addNA, factor)

formula, data

formula and by which the data should be modelled, similar to lm.

If formula is not given, the the linear model is given by the data themselves.

x,y,z,T,grid

optional. The usual arguments as in RFsimulate to define the locations where the covariates are given.

`raw`	\argRaw
`norm`	\argNorm
`addNA`	If `addNA` is `TRUE`, then an additional (linear) factor is estimated in an estimation framework. This parameter must be set in particular when `RMcovariate` passes several covariates.
`factor`	real value. From user's point of view very much the same as setting the argument `var`

The function interpolates (nearest neighbour) between the values.

RMcovariate returns an object of class RMmodel.

c, x also accept lists of data. However, its use is not in an advanced stage yet.

RMfixcov, RMmodel, RMtrend

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

z <- 0.2 + (1:10)
RFfctn(RMcovariate(z), 1:10)
RFfctn(RMcovariate(data=z, x=1:10), c(2, 2.1, 2.5, 3))