Nothing
eapmulc4 <- function (mu, RES, lam, vres, nodos1, nodos2){
RES<-as.matrix(RES)
n<-size(RES)[1]
m<-size(RES)[2]
if (n>m){
ni <- n
}
else {
ni <- m
}
k <- dim(nodos1)[1]
th <- matrix(0,1,4)
vi <- 0
st <- matrix(0,1,4)
sv <- 0
p <- matrix(0,ni)
L1 <- array(0,dim=c(k,k,k,k,k))
deno <- 0
nume1 <- 0
nume2 <- 0
nume3 <- 0
nume4 <- 0
nume5 <- 0
nume6 <- 0
nume7 <- 0
nume8 <- 0
nume9 <- 0
nume10 <- 0
for (l in 1:k){
for (t in 1:k){
for(u in 1:k){
for (b in 1:k){
for (i in 1:k){
L1[l,t,u,b,i] <- 1
for (j in 1:ni){
lamtmp <- cbind(lam[j,1],lam[j,2],lam[j,3], lam[j,4])
rlamtmp <- sqrt(lamtmp %*% (transpose(lamtmp)))
term0 <- rlamtmp %*% sqrt(nodos2[i,1]+vres[j])
term1 <- 0.399 / term0
term2 <- RES[j] - mu[j] - (lam[j,1] %*% nodos1[l,1]) - (lam[j,2] %*% nodos1[t,1]) - (lam[j,3] %*% nodos1[u,1]) - (lam[j,4] %*% nodos1[b,1])
term3 <- (term2 / term0) %*% (term2 / term0)
term4 <- exp(-0.5 * term3)
term5 <- term1 * term4
L1[l,t,u,b,i] <- L1[l,t,u,b,i] * term5
}
p <- as.matrix(L1[l,t,u,b,i] * nodos1[l,2] * nodos1[t,2] * nodos1[u,2] * nodos1[b,2] * nodos2[i,2]) # evitar named num
deno <- deno + p
nume1 <- nume1 + p * nodos1[l,1]
nume2 <- nume2 + p * nodos1[t,1]
nume3 <- nume3 + p * nodos1[u,1]
nume4 <- nume4 + p * nodos1[b,1]
nume5 <- nume5 + p * nodos2[i,1]
nume6 <- nume6 + p * nodos1[l,1] * nodos1[l,1]
nume7 <- nume7 + p * nodos1[t,1] * nodos1[t,1]
nume8 <- nume8 + p * nodos1[u,1] * nodos1[u,1]
nume9 <- nume9 + p * nodos1[b,1] * nodos1[b,1]
nume10 <- nume10 + p * nodos2[i,1] * nodos2[i,1]
}
}
}
}
}
th[1] <- nume1 / deno
th[2] <- nume2 / deno
th[3] <- nume3 / deno
th[4] <- nume4 / deno
vi <- nume5 / deno
st[1] <- sqrt(nume6 / deno - (th[1]*th[1]))
st[2] <- sqrt(nume7 / deno - (th[2]*th[2]))
st[3] <- sqrt(nume8 / deno - (th[3]*th[3]))
st[4] <- sqrt(nume9 / deno - (th[4]*th[4]))
sv <- sqrt(nume10 / deno - (vi*vi))
# reli th and PDD
reli_th <- 1 - (st^2)
reli_PDD <- 0.4159/ (0.4159 + sv^2) # nodes variance
OUT <- list("th"=th, "vi"=vi, "st"=st, "sv"=sv, "reli_th" = reli_th, "reli_PDD" = reli_PDD)
return(OUT)
}
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