Nothing
vine <- function(data,d=2,d2=2,D=4,D3=6,lambda=c(100,50),type="Rvine",order.Dvine=FALSE,m=2,cores=NULL,q=1,mod.cond=TRUE,
max.iter=51,fix.lambda=FALSE,RVM=NULL,cal.cond=FALSE,
id=NULL,test.ind=FALSE,test.cond=2,lambda.search=FALSE,lam1.vec=NULL,lam2.vec=NULL) {
if(is.null(cores)) registerDoParallel() else registerDoParallel(cores=cores)
mcoptions <- list(preschedule=FALSE)
if(!is.matrix(data)) data <- as.matrix(data)
U <- data
S <- seq(1:(dim(U)[2]))
N <- dim(U)[1]
k <- 1
if(type=="Dvine") {
Dvine <- list()
SSi <- list()
#order options
#pairwise AIC-order in the first level
help.env <- new.env()
assign("S",S,help.env)
assign("U",U,help.env)
assign("lambda",lambda,help.env)
assign("lambda.search",lambda.search,help.env)
assign("lam1.vec",lam1.vec,help.env)
assign("lam2.vec",lam2.vec,help.env)
assign("fix.lambda",fix.lambda,help.env)
assign("d",d,help.env)
assign("d2",d,help.env)
assign("D",D,help.env)
assign("max.iter",max.iter,help.env)
assign("base",base<-"B-spline",help.env)
assign("m",m,help.env)
assign("q",q,help.env)
assign("test.ind",test.ind,help.env)
dd <- (2**d)+1 # Anzahl Knoten
ddb <- dd # Anzahl Basisfunktionen
cond.dens<-0
D.struc<-1
######### independence model ###
if(test.ind) {
model.l<-pencopula(data=data[,c(1,2)],d=d,D=D,pen.order=m,base="B-spline",lambda=rep(lambda[1],2),max.iter=1,cond=FALSE,q=q,id=id,fix.lambda=fix.lambda)
assign("ck.val",get("ck.val.start",model.l),model.l)
assign("log.like",0,model.l)
assign("cAIC",-0.00000000001,model.l)
assign("AIC",0,model.l)
assign("f.hat.val",get("f.hat.val.start",model.l),model.l)
assign("indep",TRUE,model.l)
assign("indep.model",model.l,help.env)
assign("cond",FALSE,model.l)
rm(model.l)
}
#########
Index.basis.D <- matrix(NA,ddb^2,2)
Index.basis.D[,1] <- rep(seq(1,ddb),ddb)
Index.basis.D[,2] <- sort(Index.basis.D[,1])
if(order.Dvine) {
assign("order.stat","cAIC",help.env)
order.Dvine(help.env)
U <- U[,get("order",help.env)]
#org.data<-org.data[,get("order",help.env)]
}
else {
assign("order",seq(1,length(S)),help.env)
}
for ( i in 1:length(S))
{
vine.knot <- list(j1=S[i],j2=NULL,D=NULL,v=NULL, U = U[,S[i]] )
SSi <- append(SSi, list(vine.knot))
}
Dvine <- append(Dvine, list(SSi))
rm(SSi)
level <- 1
log.like <- AIC <- cAIC <- 0
if(order.Dvine) {
pairs.fit <- get("pairs.fit",help.env)
pairs.new <- get("pairs.new",help.env)
Dvine <- append(Dvine, list(foreach(i=2:length(S),.combine=list,.multicombine=TRUE,.options.multicore=mcoptions) %do% {
index.j1 <- i-1 #pairs.fit[i-1,1]
index.j2 <- i #pairs.fit[i-1,2]
rev<-FALSE
for(kk in 1:dim(pairs.new)[1]) {
if(all(pairs.new[kk,]==pairs.fit[i-1,])|all(pairs.new[kk,]==c(pairs.fit[i-1,2],pairs.fit[i-1,1]))) {
model.l <- get("fit.level1",help.env)[[kk]]
if(all(pairs.new[kk,]==c(pairs.fit[i-1,2],pairs.fit[i-1,1]))) rev<-TRUE
}
}
#vine.knot <- list(j1=index.j1,j2=index.j2,D=NULL,v=get("ck.val",model.l),U=U[,c(index.j1,index.j2)],log.like = get("log.like",model.l), AIC=get("AIC",model.l),cAIC=get("cAIC",model.l),lambda=get("lambda",model.l))
vine.knot <- list(j1=index.j1,j2=index.j2,D=NULL,v=get("ck.val",model.l),U=get("Y",model.l),log.like = get("log.like",model.l), AIC=get("AIC",model.l),cAIC=get("cAIC",model.l),lambda=get("lambda",model.l),cond=FALSE,f.hat=get("f.hat.val",model.l),indep=get("indep",model.l),rev=rev)
}))
level <- 2
SS <- Dvine[[level]]
nSS <- length(SS)
while (nSS>1)
{
SSi <- list()
for (i in 2:nSS)
{
S1 <- c(SS[[i-1]]$j1, SS[[i-1]]$j2,SS[[i-1]]$D)
S2 <- c(SS[[i]]$j1, SS[[i]]$j2,SS[[i]]$D)
index1 <- rep(TRUE,length(S1))
index2 <- rep(TRUE,length(S2))
S3 <- c()
for (j in 1:length(S1))
{
indexi <- S1[j]==S2
if (sum(indexi)>0)
{
S3 <- c(S3, S1[j])
index1[j] <- FALSE
index2[indexi] <- FALSE
}
}
if(!is.null(S3)) S3 <- sort(S3)
S1 <- S1[index1]
S2 <- S2[index2]
vine.knot <- list(j1=S1,j2=S2,D=S3,v=NULL, U = NULL, log.like = NULL, AIC = NULL)
SSi <- append(SSi, list(vine.knot))
}
Dvine <- append(Dvine, list(SSi))
level <- level + 1
SS <- Dvine[[level]]
nSS <- length(SS)
}
level <- 2
}
if(!order.Dvine) {
SS <- Dvine[[level]]
nSS <- length(SS)
while (nSS>1)
{
SSi <- list()
for (i in 2:nSS)
{
S1 <- c(SS[[i-1]]$j1, SS[[i-1]]$j2,SS[[i-1]]$D)
S2 <- c(SS[[i]]$j1, SS[[i]]$j2,SS[[i]]$D)
index1 <- rep(TRUE,length(S1))
index2 <- rep(TRUE,length(S2))
S3 <- c()
for (j in 1:length(S1))
{
indexi <- S1[j]==S2
if (sum(indexi)>0)
{
S3 <- c(S3, S1[j])
index1[j] <- FALSE
index2[indexi] <- FALSE
}
}
if(!is.null(S3)) S3 <- sort(S3)
S1 <- S1[index1]
S2 <- S2[index2]
vine.knot <- list(j1=S1,j2=S2,D=S3,v=NULL, U = NULL, log.like = NULL, AIC = NULL)
SSi <- append(SSi, list(vine.knot))
}
Dvine <- append(Dvine, list(SSi))
level <- level + 1
SS <- Dvine[[level]]
nSS <- length(SS)
}
level <- 2
Tree.l <- Dvine[[level]]
Tree.l.temp <- foreach(i=1:length(Tree.l),.combine=list,.multicombine=TRUE,.options.multicore=mcoptions) %do% {
index.j1 <- Tree.l[[i]]$j1
index.j2 <- Tree.l[[i]]$j2
new.ind<-c()
if(lambda.search) model.l<-lam.search(data=U[,c(index.j1,index.j2)],d=d,D=D,lam=lam1.vec,m=m,max.iter=max.iter,q=q,cond=FALSE,id=id,l.lam=2,fix.lambda=fix.lambda,test.ind=test.ind)
if(!lambda.search) model.l<-pencopula(data=U[,c(index.j1,index.j2)],d=d,D=D,pen.order=m,base="B-spline",lambda=rep(lambda[1],2),max.iter=max.iter,q=q,id=id,cond=FALSE,fix.lambda=fix.lambda,test.ind=test.ind)
list(j1=index.j1,j2=index.j2,D=NULL,v=get("ck.val",model.l),U=get("Y",model.l),log.like = get("log.like",model.l),AIC=get("AIC",model.l),cAIC=get("cAIC",model.l),lambda=get("lambda",model.l),cond=get("cond",model.l),f.hat=get("f.hat.val",model.l),indep=get("indep",model.l))
}
if(length(S)>2) Dvine[[level]] <- Tree.l.temp
else Dvine[[level]] <- list(Tree.l.temp)
}
log.like.vec<-AIC.vec<-cAIC.vec<-c()
if(level<length(S)) {
for(i in 1:length(Dvine[[level]])) {
log.like <- log.like+Dvine[[level]][[i]]$log.like
log.like.vec[i]<-Dvine[[level]][[i]]$log.like
AIC <- AIC+Dvine[[level]][[i]]$AIC
AIC.vec[i]<-Dvine[[level]][[i]]$AIC
cAIC <- cAIC+Dvine[[level]][[i]]$cAIC
cAIC.vec[i]<-Dvine[[level]][[i]]$cAIC
}
count<-length(Dvine[[level]])
}
else {
log.like <- log.like+Dvine[[level]][[1]]$log.like
log.like.vec<-Dvine[[level]][[1]]$log.like
AIC <- AIC+Dvine[[level]][[1]]$AIC
AIC.vec<-Dvine[[level]][[1]]$AIC
cAIC <- cAIC+Dvine[[level]][[1]]$cAIC
cAIC.vec<-Dvine[[level]][[1]]$cAIC
count<-1
}
if(length(S)>2) {
for(level in 3:length(S)) {
print(paste("level= ",level,sep=""))
Tree.l <- Dvine[[level]] # current tree in vine
Tree.l1 <- Dvine[[level-1]] # previous tree in vine, one level up
t.length <- length(Tree.l)
Tree.l.temp <- foreach(i=1:t.length,.combine=list,.multicombine=TRUE,.options.multicore=mcoptions) %do% {
UU <- new.ind<-c()
index <- list(c(Tree.l[[i]]$j1,Tree.l[[i]]$D),c(Tree.l[[i]]$j2,Tree.l[[i]]$D)) # list of involved indices in current knot, i.e {j1,D} and {j2,D}
D.index<-Tree.l[[i]]$D
len.D<-length(D.index)
p<-2+len.D
if(p>(2+D.struc)) p<-2+D.struc
for(j in 1:2) # Loop over both index sets, i.e. {j1,D} and {j2,D}
{
indexi <- sort(index[[j]])
index.ancestor <- c()
for (ml in 1:length(Tree.l1))
{
index.ancestor <- c(index.ancestor, all(indexi==sort(c(Tree.l1[[ml]]$j1,Tree.l1[[ml]]$j2,Tree.l1[[ml]]$D))))
}
ancestor.knot <- Tree.l1[index.ancestor][[1]] # Ancestor knot of j-th Element in Index set, i.e. knot with indices {j1,D} for j=1 and {j2,D} for j=2, respectively.
ord1<-c(1,2)
#if(level==3&j==1) if(ancestor.knot$rev) ord1<-c(2,1)
if(j==1&!ancestor.knot$cond) UU <-cbind(UU,hierarchbs.cond.cop(data=ancestor.knot$U,coef=ancestor.knot$v,intp=c(TRUE,FALSE)[ord1],d=d,D=D,p=2,q=q))
if(j==1&ancestor.knot$cond) UU <-cbind(UU,hierarchbs.cond.cop(data=ancestor.knot$U,coef=ancestor.knot$v,intp=c(TRUE,FALSE,rep(FALSE,dim(ancestor.knot$U)[2]-2)),d=d2,D=D3,p=dim(ancestor.knot$U)[2],q=q))
if(j==1) new.ind<-ancestor.knot$indep
#if(j==2) new.ind<-c(new.ind,ancestor.knot$indep)
ord1<-c(1,2)
#if(level==3&j==2) if(ancestor.knot$rev) ord1<-c(2,1)
if(j==2&!ancestor.knot$cond) UU <-cbind(UU,hierarchbs.cond.cop(data=ancestor.knot$U,coef=ancestor.knot$v,intp=c(FALSE,TRUE)[ord1],d=d,D=D,p=2,q=q))
if(j==2&ancestor.knot$cond) UU <-cbind(UU,hierarchbs.cond.cop(data=ancestor.knot$U,coef=ancestor.knot$v,intp=c(FALSE,TRUE,rep(FALSE,dim(ancestor.knot$U)[2]-2)),d=d2,D=D3,p=dim(ancestor.knot$U)[2],q=q))
}
if(any(new.ind)) {
model.l<-get("indep.model",help.env)
cond<-FALSE
prcomp.D<-NULL
}
else {
if(!mod.cond) {
if(lambda.search) model.l<-lam.search(data=UU,d=d,D=D,lam=lam1.vec,m=m,max.iter=max.iter,q=q,cond=FALSE,id=id,l.lam=2,fix.lambda=fix.lambda,test.ind=test.ind)
if(!lambda.search) model.l<-pencopula(data=UU,d=d,D=D,pen.order=m,base="B-spline",lambda=rep(lambda[1],2),max.iter=max.iter,q=q,id=id,cond=FALSE,fix.lambda=fix.lambda,test.ind=test.ind)
cond<-FALSE
prcomp.D<-NULL
}
if(mod.cond) {
l.lam<-2+len.D
if(l.lam>(2+D.struc)) l.lam<-2+D.struc
if(len.D<=D.struc) {
if(!cal.cond) {
if(test.cond==1) pacotestOptions=pacotestset(testType='VI')
if(test.cond==2) pacotestOptions=pacotestset(testType='ECORR')
if(test.cond==2|test.cond==1) test.res<-pacotest(UU,U[,D.index],pacotestOptions)$pValue
if(is.null(test.cond)) test.res<-0.051
if(test.res<0.05) {
UU<-cbind(UU,U[,D.index])
colnames(UU)<-NULL
cond<-TRUE
prcomp.D<-NULL
if(lambda.search) model.l<-lam.search(data=UU,d=d2,D=D3,lam=lam2.vec,m=m,max.iter=max.iter,q=q,cond=TRUE,id=id,l.lam=l.lam,fix.lambda=fix.lambda,test.ind=test.ind)
if(!lambda.search) model.l<-pencopula(data=UU,d=d2,D=D3,pen.order=m,base="B-spline",lambda=rep(lambda[2],l.lam),max.iter=max.iter,cond=TRUE,q=q,id=id,fix.lambda=fix.lambda,test.ind=test.ind)
}
else {
prcomp.D<-NULL
cond <- FALSE
if(lambda.search) model.l<-lam.search(data=UU,d=d,D=D,lam=lam1.vec,m=m,max.iter=max.iter,q=q,cond=FALSE,id=id,l.lam=2,fix.lambda=fix.lambda,test.ind=test.ind)
if(!lambda.search) model.l<-pencopula(data=UU,d=d,D=D,pen.order=m,base="B-spline",lambda=rep(lambda[1],2),max.iter=max.iter,cond=FALSE,q=q,id=id,fix.lambda=fix.lambda,test.ind=test.ind)
}
}
if(cal.cond) {
UU<-cbind(UU,U[,Tree.l[[i]]$D])
prcomp.D<-NULL
cond<-TRUE
l.lam<-2+len.D
if(l.lam>(2+D.struc)) l.lam<-2+D.struc
D.struc.temp<-min(D.struc,len.D)
if(lambda.search) model.l<-lam.search(data=UU,d=d2,D=D3,lam=lam2.vec,m=m,max.iter=max.iter,q=q,cond=TRUE,id=id,l.lam=l.lam,fix.lambda=fix.lambda,test.ind=test.ind)
if(!lambda.search) model.l<-pencopula(data=UU,d=d2,D=D3,pen.order=m,base="B-spline",lambda=rep(get("lambda",help.env)[2],l.lam),max.iter=max.iter,cond=TRUE,q=q,id=id,fix.lambda=fix.lambda,test.ind=test.ind)
}
}
if(len.D>D.struc) {
if(!cal.cond) {
if(test.cond==1) pacotestOptions=pacotestset(testType='VI')
if(test.cond==2) pacotestOptions=pacotestset(testType='ECORR')
if(test.cond==2|test.cond==1) test.res<-pacotest(UU,U[,D.index],pacotestOptions)$pValue
if(is.null(test.cond)) test.res <- 0.051
if(test.res<0.05) {
data.distr<-cal.pca(help.env,val=get("data",help.env)[,D.index])
UU<-cbind(UU,data.distr$data.distr)
prcomp.D<-data.distr$prcomp.D
colnames(UU) <- NULL
cond<-TRUE
if(lambda.search) model.l<-lam.search(data=UU,d=d2,D=D3,lam=lam2.vec,m=m,max.iter=max.iter,q=q,cond=TRUE,id=id,l.lam=dim(UU)[2],fix.lambda=fix.lambda,test.ind=test.ind)
if(!lambda.search) model.l<-pencopula(data=UU,d=d2,D=D3,pen.order=m,base="B-spline",lambda=rep(get("lambda",help.env)[2],l.lam),max.iter=max.iter,cond=TRUE,q=q,id=id,fix.lambda=fix.lambda,test.ind=test.ind)
}
else {
prcomp.D<-NULL
cond <- FALSE
if(lambda.search) model.l<-lam.search(data=UU,d=d,D=D,lam=lam1.vec,m=m,max.iter=max.iter,q=q,cond=FALSE,id=id,l.lam=2,fix.lambda=fix.lambda,test.ind=test.ind)
if(!lambda.search) model.l<-pencopula(data=UU,d=d,D=D,pen.order=m,base="B-spline",lambda=rep(lambda[1],2),max.iter=max.iter,cond=FALSE,q=q,id=id,fix.lambda=fix.lambda,test.ind=test.ind)
}
}
if(cal.cond) {
data.distr<-cal.pca(help.env,val=get("data",help.env)[,D.index])
UU<-cbind(UU,data.distr$data.distr)
prcomp.D<-data.distr$prcomp.D
colnames(UU) <- c()
l.lam<-2+len.D
if(l.lam>(2+D.struc)) l.lam<-2+D.struc
cond<-TRUE
if(lambda.search) model.l<-lam.search(data=UU,d=d2,D=D3,lam=lam2.vec,m=m,max.iter=max.iter,q=q,cond=TRUE,id=id,l.lam=l.lam,fix.lambda=fix.lambda,test.ind=test.ind)
if(!lambda.search) model.l<-pencopula(data=UU,d=d2,D=D3,pen.order=m,base="B-spline",lambda=rep(get("lambda",help.env)[2],l.lam),max.iter=max.iter,cond=TRUE,q=q,id=id,fix.lambda=fix.lambda,test.ind=test.ind)
}
}
}
}
list(j1=Tree.l[[i]]$j1,j2=Tree.l[[i]]$j2,D=Tree.l[[i]]$D,U=UU,v=get("ck.val",model.l),log.like = get("log.like",model.l),AIC=get("AIC",model.l),cAIC=get("cAIC",model.l),lambda=get("lambda",model.l),cond=cond,prcomp.D=prcomp.D,f.hat=get("f.hat.val",model.l),indep=get("indep",model.l))
}
if(level<length(S)) {
for(i in 1:length(Tree.l.temp)) {
log.like <- log.like+Tree.l.temp[[i]]$log.like
log.like.vec[i+count]<-Tree.l.temp[[i]]$log.like
AIC <- AIC+Tree.l.temp[[i]]$AIC
AIC.vec[i+count]<-Tree.l.temp[[i]]$AIC
cAIC <- cAIC+Tree.l.temp[[i]]$cAIC
cAIC.vec[i+count]<-Tree.l.temp[[i]]$cAIC
cond.dens<-cond.dens+Tree.l.temp[[i]]$cond
}
count<-count+i
}
else {
log.like <- log.like+Tree.l.temp$log.like
log.like.vec[1+count]<-Tree.l.temp$log.like
AIC <- AIC+Tree.l.temp$AIC
AIC.vec[1+count]<-Tree.l.temp$AIC
cAIC <- cAIC+Tree.l.temp$cAIC
cAIC.vec[1+count]<-Tree.l.temp$cAIC
cond.dens<-cond.dens+Tree.l.temp$cond
Tree.l.temp <- list(Tree.l.temp)
}
Dvine[[level]] <- Tree.l.temp
}
}
class(vine) <- "pencopulaCond"
return(list(Dvine=Dvine,log.like=log.like,log.like.vec=log.like.vec,AIC=AIC,AIC.vec=AIC.vec,cAIC=cAIC,cAIC.vec=cAIC.vec,d=d,d2=d2,D=D,D3=D3,order=get("order",help.env),S=S,N=N,q=q,no.cond.dens=cond.dens,D.struc=D.struc,type=type))
}
if(type=="Rvine") {
vine <- list()
SSi <- list()
help.env <- new.env()
#if(is.null(lam.vec)&l.search) lam.vec<-c(10,seq(50,1550,by=250))
assign("lam1.vec1",lam1.vec,help.env)
assign("lam2.vec2",lam2.vec,help.env)
assign("fix.lambda",fix.lambda,help.env)
assign("lambda.search",lambda.search,help.env)
assign("test.ind",test.ind,help.env)
assign("test.cond",test.cond,help.env)
assign("S",S,help.env)
assign("max.iter",max.iter,help.env)
assign("p",length(S),help.env)
assign("U",U,help.env)
assign("lambda",lambda,help.env)
assign("base",base<-"B-spline",help.env)
assign("d",d,help.env)
assign("d2",d2,help.env)
assign("D",D,help.env)
assign("D3",D3,help.env)
assign("base",base,help.env)
assign("m",m,help.env)
assign("q",q,help.env)
dd <- (2**d)+1 # Anzahl Knoten
ddb <- dd # Anzahl Basisfunktionen
assign("order.stat","cAIC",help.env)
assign("selec","cAIC",help.env)
assign("id",id,help.env)
assign("test.ind",test.ind,help.env)
D.struc<-1
assign("D.struc",D.struc,help.env)
if(!is.null(RVM)) assign("RVM",reRVineMatrix(help.env),help.env)
order.vine(help.env,test.ind=test.ind)
for ( i in 1:length(S))
{
vine.knot <- list(j1=S[i],j2=NULL,D=NULL,v=NULL, U = U[,S[i]],follow=c())
SSi <- append(SSi, list(vine.knot))
}
vine <- append(vine, list(SSi))
rm(SSi)
level <- 1
log.like.vec<-AIC.vec<-cAIC.vec<-c()
log.like <- AIC <- cAIC <- cond.dens<-0
pairs.fit <- get("pairs.fit",help.env)
pairs.new <- get("pairs.new",help.env)
mcoptions<-list(preschedule=FALSE)
vine <- append(vine, list(foreach(i=2:length(S),.combine=list,.multicombine=TRUE,.options.multicore=mcoptions) %dopar% {
index.j1 <- pairs.fit[i-1,1]
index.j2 <- pairs.fit[i-1,2]
if(get("selec",help.env)=="cAIC") {
for(kk in 1:dim(pairs.new)[1]) {
if(all(pairs.new[kk,]==pairs.fit[i-1,])) model.l <- get("fit.level2",help.env)[[kk]]
}
}
if(get("selec",help.env)=="ken.tau") model.l <- get("fit.level2",help.env)[[i-1]]
dim2<-length(model.l)
vine.knot <- list(j1=index.j1,j2=index.j2,D=NULL,v=model.l$v,U=U[,c(index.j1,index.j2)],log.like = model.l$log.like, AIC=model.l$AIC,cAIC=model.l$cAIC,lambda=model.l$lambda,f.hat=model.l$f.hat,Index.basis.D=model.l$Index.basis.D,ddb=model.l$ddb,cond=FALSE)
}))
foreach(i=2:length(S),.combine=list,.multicombine=TRUE,.options.multicore=mcoptions) %dopar% {
index.j1 <- pairs.fit[i-1,1]
index.j2 <- pairs.fit[i-1,2]
vine[[level]][[index.j1]]$follow <- c(vine[[level]][[index.j1]]$follow,i-1)
vine[[level]][[index.j2]]$follow <- c(vine[[level]][[index.j2]]$follow,i-1)
vine[[level+1]][[i-1]]$before <- c(vine[[level]][[i-1]]$before,pairs.fit[i-1,1],pairs.fit[i-1,2])
}
rm(list=c("fit.level2"),envir=help.env)
level <- 2
assign("level",level,help.env)
for(i in 1:length(vine[[level]])) {
log.like <- log.like+vine[[level]][[i]]$log.like
log.like.vec[i]<-vine[[level]][[i]]$log.like
AIC <- AIC+vine[[level]][[i]]$AIC
AIC.vec[i]<-vine[[level]][[i]]$AIC
cAIC <- cAIC+vine[[level]][[i]]$cAIC
cAIC.vec[i]<-vine[[level]][[i]]$cAIC
}
count<-length(vine[[level]])
assign("rest.indep",FALSE,help.env)
for(level in 3:length(S)) {
print(paste("level=",level,sep=""))
assign("level",level,help.env)
Tree.l1 <- vine[[level-1]]
order.vine.level(tree=Tree.l1,help.env)
pairs.fit <- get("pairs.fit",help.env)
pairs.new <- get("pairs.new",help.env)
vine <- append(vine, vinepart <- list(foreach(i=1:dim(pairs.fit)[1],.combine=list,.multicombine=TRUE,.options.multicore=mcoptions) %do% {
help.j1 <- c(Tree.l1[[pairs.fit[i,1]]]$j1,Tree.l1[[pairs.fit[i,1]]]$j2,Tree.l1[[pairs.fit[i,1]]]$D)
help.j2 <- c(Tree.l1[[pairs.fit[i,2]]]$j1,Tree.l1[[pairs.fit[i,2]]]$j2,Tree.l1[[pairs.fit[i,2]]]$D)
index.j1 <- help.j1[!help.j1%in%help.j2]#Vorgaenger
index.j2 <- help.j2[!help.j2%in%help.j1]#
D.help <- c(Tree.l1[[pairs.fit[i,1]]]$D,Tree.l1[[pairs.fit[i,2]]]$D)
D <- sort(unique(c(help.j1[help.j1%in%help.j2],D.help)))
if(get("selec",help.env)=="cAIC") {
if(dim(pairs.new)[1]==1) model.l<-get(paste("fit.level",level,sep=""),help.env)
if(dim(pairs.new)[1]>1) {
for(kk in 1:dim(pairs.new)[1]) {
if(all(pairs.new[kk,]==pairs.fit[i,])) model.l <- get(paste("fit.level",level,sep=""),help.env)[[kk]]
}
}
}
if(get("selec",help.env)=="ken.tau") model.l <- get(paste("fit.level",level,sep=""),help.env)[[i]]
list(j1=index.j1,j2=index.j2,D=D,U=get("Y",model.l),v=get("ck.val",model.l),log.like = get("log.like",model.l), AIC=get("AIC",model.l),cAIC=get("cAIC",model.l),lambda=get("lambda",model.l),f.hat=get("f.hat.val",model.l),Index.basis.D=get("Index.basis.D",model.l),ddb=get("ddb",model.l),cond=get("cond",model.l),prcomp.D=get("prcomp.D",model.l),indep=get("indep",model.l))
}))
if(dim(pairs.new)[1]==1) {
vine[[level]]<-list(vine[[level]])
vinepart<-list(vinepart)
}
foreach(i=1:dim(pairs.fit)[1],.options.multicore=mcoptions,.multicombine=TRUE) %do% {
index.j1 <- pairs.fit[i,1]
index.j2 <- pairs.fit[i,2]
vine[[level-1]][[index.j1]]$follow <- c(vine[[level-1]][[index.j1]]$follow,i)
vine[[level-1]][[index.j2]]$follow <- c(vine[[level-1]][[index.j2]]$follow,i)
vine[[level]][[i]]$before <- c(vine[[level]][[i]]$before,pairs.fit[i,1],pairs.fit[i,2])
}
add.VineMatrix(vinepart[[1]],help.env,level)
for(i in 1:length(vinepart[[1]])) {
log.like <- log.like+vinepart[[1]][[i]]$log.like
log.like.vec[i+count]<-vinepart[[1]][[i]]$log.like
AIC <- AIC+vinepart[[1]][[i]]$AIC
AIC.vec[i+count]<-vinepart[[1]][[i]]$AIC
cAIC <- cAIC+vinepart[[1]][[i]]$cAIC
cAIC.vec[i+count]<-vinepart[[1]][[i]]$cAIC
cond.dens<-cond.dens+vinepart[[1]][[i]]$cond
}
count<-count+i
rm(list=c(paste("fit.level",level,sep="")),pos=help.env)
if(all(foreach(i=1:length(vine[[level]]),.combine=c) %do% vine[[level]][[i]]$indep)) assign("rest.indep",TRUE,help.env)
}
RVineMatrix(help.env)
data.est <- rep(1,dim(data)[1])
for(i in 2:length(S)) {
for(j in 1:length(vine[[i]])) {
data.est <- data.est*vine[[i]][[j]]$f.hat
}
}
class(vine) <- "pencopulaCond"
return(list(Dvine=vine,log.like=log.like,log.like.vec=log.like.vec,AIC=AIC,AIC.vec=AIC.vec,cAIC=cAIC,cAIC.vec=cAIC.vec,d=get("d",help.env),d2=d2,D=get("D",help.env),D3=D3,S=S,N=N,base=base,q=q,no.cond.dens=cond.dens,D.struc=D.struc,type=type,VineMatrix=get("VineMatrix",help.env)))
}
}
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