# RFlinearpart: Linear part of 'RMmodel' In RandomFields: Simulation and Analysis of Random Fields

## Description

`RFlinearpart` returns the linear part of a model

## Usage

 ```1 2``` ```RFlinearpart(model, x, y = NULL, z = NULL, T = NULL, grid=NULL, data, params, distances, dim, set=0, ...) ```

## Arguments

 `model,params` \argModel `x` \argX `y,z` \argYz `T` \argT `grid` \argGrid `distances,dim` \argDistances `data` \argData `set` integer. See section Value for details. `...` \argDots

## Value

`RFlinearpart` returns a list of three components, `Y`, `X`, `vdim` returning the deterministic trend, the design matrix, and the multivariability, respectively. If `set` is positive, `Y` and `X` contain the values for the `set`-th set of coordinates. Else, `Y` and `X` are both lists containing the values for all the sets.

## Note

In the linear part of the model specification the parameters that are NA must be the first model part. I.e. `NA * sin(R.p(new="isotropic")) + NA + R.p(new="isotropic")` is OK, but not `sin(R.p(new="isotropic")) * NA + NA + R.p(new="isotropic")`

Bayesian, `RMmodel`, `RFsimulate`, `RFlikelihood`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again x <- seq(0, pi, len=10) trend <- 2 * sin(R.p(new="isotropic")) + 3 model <- RMexp(var=2, scale=1) + trend print(RFlinearpart(model, x=x)) ## only a deterministic part trend <- NA * sin(R.p(new="isotropic")) + NA + R.p(new="isotropic") / pi model <- RMexp(var=NA, scale=NA) + trend print(RFlinearpart(model, x=x)) ```