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gradvec
2007 Jun 15
0
Question with nlm
...*% invQ %*% (y- xM %*% Bt);
# log likelihood function
loglik <- -0.5*log(abs(det(diag(rep(sigma2,totalTime)))))-0.5*log(abs(det(Q)))-
(0.5/sigma2)* (t(y- (xM%*% Bt)) %*% invQ %*% (y-(xM %*% Bt)));
sgm <- sigma;
# gradients eq. (4.16)
gr <- function(sgm) {
gradVecs <- c();
# sgm <- c(sigma1, sigma2);
sgm <- sgm*sgm;
for (i in 1:length(sgm)) {
Eij <- matrix(rep(0, length(sgm)^2), nrow=length(sgm), ncol=length(sgm));
Eij[i,i] <- 1.0;
# trace term
term1 <- -sum(diag((invQ %*% A) %*% o...
2010 Mar 27
1
R runs in a usual way, but simulations are not performed
Dear addresses, I need perform a batch of 10 000 simulations for each of
4 options considered. (The idea is to obtain the parameter estimates in
a heteroskedastic linear regression model - with additive or mixed
heteroskedasticity - via the Kenward-Roger small-sample adjusted
covariance matrix of disturbances). For this purpose I wrote an R
program which would capture all possible options (true