Marginal MLEs for the Fay-Herriot model with known covariance

Marginal MLEs for the Fay-Herriot random effects model where the covariance matrix for the sampling model is known

mmleFHP(y, X, Sigma)

Arguments

y

direct data following normal model \(y\sim N(\theta,\Sigma)\)
X

linking model predictors \( \theta\sim N(X\beta,\tau^2 I)\)
Sigma

covariance matrix in sampling model

Value

a list of parameter estimates including

  1. beta, the estimated regression coefficients

  2. t2, the estimate of \(\tau^2\)

Author

Peter Hoff

Examples

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) 

#> $beta
#>        Xd1        Xd2        Xd3 
#> -0.5169015  0.4703897 -0.9970674 
#> 
#> $t2
#> [1] 0.6564275
#>