R/Par.dlrm.R

In StVAR: Student's t Vector Autoregression (StVAR)

Par.dlrm <-
function(a,S,MU,l,lag,v,T,M,c,TREND)
{
###########################Parameters##################
TREND <- TREND

S <- BlockTop(a[((l*(l+1)/2)*(1-1)+1):((lag+3)*(l+1)*l/2)],l,lag)$S
if(c!=0) {MU <- matrix(c(a[(((lag+3)*(l+1)*l/2)+1):(((lag+3)*(l+1)*l/2)+l*c)]),l,c)}

if(c!=0) {M0 <- kronecker(diag(1,lag+1),MU)}
if(c==0) {M0 <- kronecker(diag(1,lag+1),0)}

if(c!=0) {M <- M0%*%t(TREND)} ; if (c==0) {M <- 0}

S11 <- S[1:1,1:1] ; S12 <- S[1:1,(1+1):ncol(S)] ; S22 <- S[(1+1):ncol(S),(1+1):ncol(S)]
SS <- solve(S22)  ; Q <- SS/v ; B1 <- SS%*%(S12) ; s2 <- S11-S12%*%SS%*%(S12) 

if(c!=0) {Delta0 <- MU[1:1,] - t(B1)%*%MU[c(2:l,rep(1:l,lag)),]}
if(c==0) {Delta0 <- 0}
beta <- cbind(Delta0, t(B1))

c.var <- (s2[1,1]*vech(SS)/(v+l*lag-2))
var.coef <- c(v*s2[1,1]/(v+l*lag-2),c.var)

return(list(Delta0=Delta0,Q=Q,s2=s2,S=S,B1=B1,var.coef=var.coef))

}