mubz.normal: mu(B,z) for the Gaussian model
In HiDimMaxStable: Inference on High Dimensional Max-Stable Distributions

Description Usage Arguments Details See Also Examples

Computes mu(B,z) for the Gaussian model.

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mubz.normal(b,z,params=NULL,spatial=NULL,
    cor.matrix=spatial.cor.matrix(c(params,1),spatial),
    details=FALSE)

`b`	a vector of TRUE or FALSE, of length `d` where `d=length(z)`, TRUE indicating the coordinates of B
`z`	a vector of positive constants
`params`	a vector of length 2 that must be informed if `spatial` is given; the first component is for the range parameter and the second component is for the smoothness parameter
`spatial`	the correlation model given as a list: `spatial$sites` is a matrix that gives the coordinates of each location. Each row corresponds to one location. `spatial$family` is a object from the `spatial` class that gives the spatial model. This must be one of the following family: `spatialWhittleMatern` for the Whittle Matern correlation model, `spatialCauchy` for the Cauchy correlation model, `spatialPowerExp` for the Power exponential model, `spatialBessel` for the Bessel correlation model
`cor.matrix`	a correlation matrix if `spatial=NULL`
`details`	get more details in the return value?

mubz.normal uses mnormpow to compute the value of mu(B,z). If the dimension of z is too large (cannot exceed 20), the computation may fail.

mubz.lnormal, mubz.copula

# In this example, we compute mu(B,z) for Whittle Matern spatial model
# from 10 sites uniformly distributed on the square [0,2]x[0,2]
mubz.normal(b=c(TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE),
    z=rep(1,10),params=c(1,2),
    spatial=list(sites=matrix(2*runif(20),ncol=2),family=spatialWhittleMatern))