R: Linear part of 'RMmodel'

RFlinearpart {RandomFields} | R Documentation

## Linear part of `RMmodel`

### Description

`RFlinearpart` returns the linear part of a model

### Usage

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

### Arguments

`model` | object of class `RMmodel`; the covariance or variogram model, which is to be evaluated
`x` | vector or (n x \code{dim})-matrix, where n is the number of points at which the covariance function is to be evaluated; in particular, if the model is isotropic or `dim=1` then `x` is a vector. `x`
`y` | second vector or matrix for non-stationary covariance functions
`z` | z-component of point if xyzT-specification of points is used
`T` | T-component of point if xyzT-specification of points is used
`grid` | boolean; whether xyzT specify a grid
`data` | vector or matrix of values measured at `coord`; If a matrix is given then the columns are interpreted as independent realisations. If also a time component is given, then in the data the indices for the spatial components run the fastest. If an `m`-variate model is used, then each realisation is given as `m` consecutive columns of `data`.
`distances` | vector; the lower triangular part of the distance matrix column-wise; equivalently the upper triangular part of the distance matrix row-wise; either `x` or `distances` must be missing
`dim` | dimension of the coordinate space in which the model is applied; only necesary for given `distances`
`set` | integer. See section Value for details.
`...` | for advanced further options and control arguments for the simulation that are passed to and processed by `RFoptions`

### 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")`

### Author(s)

Martin Schlather, schlather@math.uni-mannheim.de http://ms.math.uni-mannheim.de/de/publications/software

### See Also

Bayesian, `RMmodel`, `RFsimulate`, `RFlikelihood`.

### Examples

    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))

[Package RandomFields version 3.1.50 Index]