# RFcovmatrix: Covariance matrix In RandomFields: Simulation and Analysis of Random Fields

## Description

`RFcovmatrix` returns the covariance matrix for a set of points;

## Usage

 ```1 2``` ```RFcovmatrix(model, x, y = NULL, z = NULL, T = NULL, grid, params, distances, dim,...) ```

## Arguments

 `model,params` \argModel `x` \argX `y,z` \argYz `T` \argT `grid` \argGrid `distances,dim` \argDistances `...` \argDots

## Details

`RFcovmatrix` returns a covariance matrix. Here, a matrix of coordinates (`x`) or a vector or a matrix of `distances` is expected.

`RFcovmatrix` also allows for variogram models. Then the negative of the variogram matrix is returned.

## Value

`RFcovmatrix` returns a covariance matrix.

`RMmodel`, `RFsimulate`, `RFfit`, `RFfctn`, `RFcalc`, `RFcov`, `RFpseudovariogram`, `RFvariogram`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```################################################## # Example: get covariance matrix C(x_i,x_j) # at given locations x_i, i=1,...,n # # here for an isotropic stationary covariance model # yields a 4 times 4 covariance matrix of the form # C(0) C(5) C(3) C(2.5) # C(5) C(0) C(4) C(2.5) # C(3) C(4) C(0) C(2.5) # C(2.5) C(2.5) C(2.5) C(0) model <- RMexp() # the covariance function C(x,y)=C(r) of this model # depends only on the distance r between x and y RFcovmatrix(model=model, distances=c(5,3,2.5,4,2.5,2.5), dim=4) ```