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

## Description

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

## Usage

 ```1 2 3``` ```mubz.normal(b,z,params=NULL,spatial=NULL, cor.matrix=spatial.cor.matrix(c(params,1),spatial), details=FALSE) ```

## Arguments

 `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?

## Details

`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`
 ```1 2 3 4 5``` ```# 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)) ```