makeSigmaB: Create Block Covariance Matrix (Equal Block Sizes)
In SpatioTemporal: Spatio-Temporal Model Estimation

Description Usage Arguments Details Value Author(s) See Also Examples

Function that creates a block covariance matrix with equal sized blocks. Used to construct the Sigma_B matrix.

1 2	makeSigmaB(pars, dist, type = "exp", nugget = 0, symmetry = dim(dist)[1] == dim(dist)[2], ind2.to.1 = 1:dim(dist)[2], sparse = FALSE, diff = 0)

`pars`	List of parameters for each block; if not a list a single block matrix is assumed. Should match parameters suggested by `parsCovFuns`.
`dist`	Distance matrix.
`type`	Name(s) of covariance functions, see `namesCovFuns`.
`nugget`	Vector of nugget(s) to add to the diagonal of each matrix.
`symmetry`	`TRUE`/`FALSE` flag if the `dist` is symmetric, resulting in a symmetric covariance matrix.
`ind2.to.1`	Vectors, that for each index along the second dimension gives a first dimension index, used only if `symmetry=FALSE` to determine which covariances should have an added nugget (collocated sites).
`sparse`	If `TRUE`, return a block diagonal sparse matrix, see `bdiag.spam`.
`diff`	Vector with two components indicating with respect to which parameter(s) that first and/or second derivatives should be computed. E.g. `diff=c(0,0)` indicates no derivatives, `diff=c(1,0)` indicates first derivative wrt the first parameter, `diff=c(1,2)` indicates second cross derivative wrt the first and second parameters, etc.

Any parameters given as scalars will be rep-ed to match length(pars).

Block covariance matrix of size dim(dist)*n.blocks.

Johan Lindstrom

Other block matrix functions: blockMult, calc.FXtF2, calc.FX, calc.mu.B, calc.tFXF, calc.tFX, makeCholBlock, makeSigmaNu

Other covariance functions: crossDist, evalCovFuns, makeSigmaNu, namesCovFuns, parsCovFuns, updateCovf

##First create some random locations
x <- rnorm(5)
y <- rnorm(5)

##compute distance matrix
D <- crossDist( cbind(x,y) )

##create a block diagonal matrix exponential covariance matrix
##with different range, sill, and nugget
pars <- list(c(.3,2), c(2,1), c(1,3))
nugget <- c(.5,0,1)

Sigma1 <- makeSigmaB(pars, D, type="exp", nugget=nugget)
##or using different covariance functions for each block
Sigma2 <- makeSigmaB(pars, D, type=c("exp","exp2","cubic"),
                     nugget=nugget)

##make a cross-covariance matrix
Dcross <- D[1:3,c(1,1,2,2)]
Sigma.cross <- makeSigmaB(pars, Dcross, type="exp", nugget=nugget,
                          ind2.to.1=c(1,1,2,2))