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# The 'stcov' function is defined as, per (Pfeifer & Stuart, 1980), the
# following expression:
# cov(l,k,s) = E[ (W(l)*z(t))' * (W(k)*z(t+s)) ] / N
# = Tr( W(k)'*W(l) * E[z(t)*z(t+s)'] ) / N
stcov <- function(data, wlist, slag1, slag2, tlag) {
if (is.matrix(wlist))
wlist <- list(diag(dim(wlist)[1]), wlist)
if (is.data.frame(data))
return(stcovCPP(as.matrix(data), wlist, slag1, slag2, tlag))
else
return(stcovCPP(data, wlist, slag1, slag2, tlag))
}
# Ideas to optimize code:
# - Try to export data.frame into C++, since converting it into a matrix
# beforehand takes a lot of time.
# - Try to express wlist in a RcppArmadillo native code. As it is, it must
# create two matrices w1 and w2.
# - Using sparse matrices for weight matrices.
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