# NOT RUN {
complex_CF(c(1,1i),c(1,-1i),means=c(1i,1i),pos.def.matrix=diag(2))
V <- latin.hypercube(7,2,complex=TRUE)
cm <- c(1,1+1i) # "complex mean"
cs <- matrix(c(2,1i,-1i,1),2,2) # "complex scales"
tb <- c(1,1i,1-1i) # "true beta"
A <- corr_complex(V,means=cm,pos.def.matrix=cs)
Ainv <- solve(A)
z <- drop(rcmvnorm(n=1,mean=regressor.multi(V) %*% tb, sigma=A))
betahat.fun(V,Ainv,z) # should be close to 'tb'
#scales.likelihood.complex(cs,cm,V,z) # log-likelihood evaluated true parameters
interpolant.quick.complex(x=0.1i+V[1:3,],d=z,zold=V,Ainv=Ainv,pos.def.matrix=cs,means=cm)
# }
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