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Marginal MLEs for the Fay-Herriot random effects model where the covariance matrix for the sampling model is known
mmleFHP(y, X, Sigma)
direct data following normal model \(y\sim N(\theta,\Sigma)\)
linking model predictors \( \theta\sim N(X\beta,\tau^2 I)\)
covariance matrix in sampling model
a list of parameter estimates including
beta, the estimated regression coefficients
t2, the estimate of \(\tau^2\)
# NOT RUN { n<-30 ; p<-3 X<-matrix(rnorm(n*p),n,p) beta<-rnorm(p) theta<-X%*%beta + rnorm(n) Sigma<-diag(n) y<-theta+rnorm(n) mmleFHP(y,X,Sigma) # }
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