Nothing
LW.grad <-
function(w,theta.l,mu.l,sigma.v,ind=500,nproc=10,n,m,X,l.b,u.b,N.s,files){
# added following lines to avoid notes in package
# files=get("files");
# n=get("n");
# m=get("m");
# X=get("X");
# l.b=get("l.b");
# u.b=get("u.b");
# N.s=get("N.s");
load(files[1])
fe=matrix(0,n,m)
feg=matrix(0,n,m)
fegg=matrix(0,n,m)
grad=c()
gradnn=c()
res=c()
w1=t(w[[1]])
winv=solve(w1)
x1=t(X)
mult=pmin(pmax(x1%*%w1,l.b),u.b)
# compute the density values for each column
for(j in 1:m){
fapp=fhatnew(mult[,j],theta.l[[j]],mu.l[[j]],sigma.v[j])
fe[,j]=fapp[,1]
feg[,j]=fapp[,2]
}
fegfe=feg/fe
#
# for(subj in 1:N.s){
# w1=t(w[[subj]])
# winv=solve(w1)
# load(files[subj])
# x1=t(X)
#
# gradn=matrix(0,m*m,n)
# for(k in 1:m){
# for(j in 1:m){
# gradn[((k-1)*m+1)+j-1,]=x1[,j]*fegfe[,k]+t(winv)[j,k]
# }
# }
# grad=apply(gradn,1,sum)
#
# mind=floor(n/ind)
# hes=0
# for(i in 1:mind){
# hes=hes+gradn[,((i-1)*ind+1):(i*ind)]%*%t(gradn[,((i-1)*ind+1):(i*ind)])}
# if((mind*ind)<n){
# hes=hes+gradn[,(mind*ind+1):n]%*%t(gradn[,(mind*ind+1):n])}
#
# res=c(res,list(solve(hes)%*%grad))
# }
# if(par==0){
# options(sge.trace=TRUE)
# options(sge.debug=FALSE)
# options(sge.use.cluster=FALSE);
# res=sge.parLapply(1:N.s,parcom,w,files,m,n,fegfe,ind,njobs=30)
# options(sge.use.cluster=TRUE)
# }
# if(par==1){
# res=sge.parLapply(1:N.s,parcom,w,files,m,n,fegfe,ind,njobs=30)
# }
# if(par==2){
# cl=makeSOCKcluster(c("localhost","localhost"))
# cl=makeSOCKcluster(rep("localhost",nproc))
cl = makeCluster(nproc)
res=parSapply(cl,X=1:N.s,parcom,w,files,m,n,fegfe,ind,X)
stopCluster(cl)
# res = sapply(1:N.s,parcom,w,files,m,n,fegfe,ind,X)
# }
return(res)
}
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