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cdssden <- ## Evaluate conditional density
function (object,x,cond,int=NULL) {
if (!("ssden"%in%class(object))) stop("gss error in cdssden: not a ssden object")
if (nrow(cond)!=1) stop("gss error in cdssden: condition has to be a single point")
xnames <- NULL
for (i in colnames(object$mf))
if (all(i!=colnames(cond))) xnames <- c(xnames,i)
if (any(length(xnames)==c(0,ncol(object$mf))))
stop("gss error in cdssden: not a conditional density")
if (length(xnames)==1&is.vector(x)) {
x <- data.frame(x)
colnames(x) <- xnames
}
if (!all(sort(xnames)==sort(colnames(x))))
stop("gss error in cdssden: mismatched variable names")
## Calculate normalizing constant
while (is.null(int)) {
fac.list <- NULL
num.list <- NULL
for (xlab in xnames) {
if (is.factor(x.wk <- x[[xlab]])) fac.list <- c(fac.list,xlab)
else {
if (!is.vector(x.wk)|is.null(object$domain[[xlab]])) {
warning("gss warning in cdssden: int set to 1")
int <- 1
next
}
else num.list <- c(num.list,xlab)
}
}
## Generate quadrature for numerical variables
if (!is.null(num.list)) {
if (length(num.list)==1) {
## Gauss-Legendre quadrature
mn <- min(object$domain[,num.list])
mx <- max(object$domain[,num.list])
quad <- gauss.quad(200,c(mn,mx))
quad$pt <- data.frame(quad$pt)
colnames(quad$pt) <- num.list
}
else {
## Smolyak cubature
domain.wk <- object$domain[,num.list]
code <- c(15,14,13)
quad <- smolyak.quad(ncol(domain.wk),code[ncol(domain.wk)-1])
for (i in 1:ncol(domain.wk)) {
xlab <- colnames(domain.wk)[i]
form <- as.formula(paste("~",xlab))
jk <- ssden(form,data=object$mf,domain=domain.wk[i],alpha=2,
id.basis=object$id.basis)
quad$pt[,i] <- qssden(jk,quad$pt[,i])
quad$wt <- quad$wt/dssden(jk,quad$pt[,i])
}
jk <- NULL
quad$pt <- data.frame(quad$pt)
colnames(quad$pt) <- colnames(domain.wk)
}
}
else quad <- list(pt=data.frame(dum=1),wt=1)
## Incorporate factors in quadrature
if (!is.null(fac.list)) {
for (i in 1:length(fac.list)) {
wk <- expand.grid(levels(object$mf[[fac.list[i]]]),1:length(quad$wt))
quad$wt <- quad$wt[wk[,2]]
col.names <- c(fac.list[i],colnames(quad$pt))
quad$pt <- data.frame(wk[,1],quad$pt[wk[,2],])
colnames(quad$pt) <- col.names
}
}
xmesh <- quad$pt[,xnames,drop=FALSE]
xx <- cond[rep(1,nrow(xmesh)),,drop=FALSE]
int <- sum(dssden(object,cbind(xmesh,xx))*quad$wt)
}
## Return value
xx <- cond[rep(1,nrow(x)),,drop=FALSE]
list(pdf=dssden(object,cbind(x,xx))/int,int=int)
}
cpssden <- ## Compute cdf for univariate conditional density
function(object,q,cond) {
if (!("ssden"%in%class(object))) stop("gss error in cpssden: not a ssden object")
xnames <- NULL
for (i in colnames(object$mf))
if (all(i!=colnames(cond))) xnames <- c(xnames,i)
if ((length(xnames)!=1)|!is.vector(object$mf[,xnames]))
stop("gss error in cpssden: not a 1-D conditional density")
mn <- min(object$domain[,xnames])
mx <- max(object$domain[,xnames])
order.q <- rank(q)
p <- q <- sort(q)
q.dup <- duplicated(q)
p[q<=mn] <- 0
p[q>=mx] <- 1
qd.hize <- 200
qd <- gauss.quad(2*qd.hize,c(mn,mx))
d.qd <- cdssden(object,qd$pt,cond)$pdf
gap <- diff(qd$pt)
g.wk <- gap[qd.hize]/2
for (i in 1:(qd.hize-2)) g.wk <- c(g.wk,gap[qd.hize+i]-g.wk[i])
g.wk <- 2*g.wk
g.wk <- c(g.wk,(mx-mn)/2-sum(g.wk))
gap[qd.hize:1] <- gap[qd.hize+(1:qd.hize)] <- g.wk
brk <- cumsum(c(mn,gap))
kk <- (1:length(q))[q>mn&q<mx]
for (i in kk) {
if (q.dup[i]) {
p[i] <- p.dup
next
}
ind <- (1:(2*qd.hize))[qd$pt<q[i]]
if (!length(ind)) {
wk <- d.qd[1]*qd$wt[1]*(q[i]-mn)/gap[1]
}
else {
wk <- sum(d.qd[ind]*qd$wt[ind])
id.mx <- max(ind)
if (q[i]<brk[id.mx+1])
wk <- wk-d.qd[id.mx]*qd$wt[id.mx]*(brk[id.mx+1]-q[i])/gap[id.mx]
else wk <- wk+d.qd[id.mx+1]*qd$wt[id.mx+1]*(q[i]-brk[id.mx+1])/gap[id.mx+1]
}
p[i] <- p.dup <- wk
}
p[order.q]
}
cqssden <- ## Compute quantiles for univariate conditional density
function(object,p,cond) {
if (!("ssden"%in%class(object))) stop("gss error in cqssden: not a ssden object")
xnames <- NULL
for (i in colnames(object$mf))
if (all(i!=colnames(cond))) xnames <- c(xnames,i)
if ((length(xnames)!=1)|!is.vector(object$mf[,xnames]))
stop("gss error in cqssden: not a 1-D conditional density")
mn <- min(object$domain[,xnames])
mx <- max(object$domain[,xnames])
order.p <- rank(p)
q <- p <- sort(p)
p.dup <- duplicated(p)
q[p<=0] <- mn
q[p>=1] <- mx
qd.hize <- 200
qd <- gauss.quad(2*qd.hize,c(mn,mx))
d.qd <- cdssden(object,qd$pt,cond)$pdf
gap <- diff(qd$pt)
g.wk <- gap[qd.hize]/2
for (i in 1:(qd.hize-2)) g.wk <- c(g.wk,gap[qd.hize+i]-g.wk[i])
g.wk <- 2*g.wk
g.wk <- c(g.wk,(mx-mn)/2-sum(g.wk))
gap[qd.hize:1] <- gap[qd.hize+(1:qd.hize)] <- g.wk
brk <- cumsum(c(mn,gap))
p.wk <- cumsum(d.qd*qd$wt)
kk <- (1:length(p))[p>0&p<1]
for (i in kk) {
if (p.dup[i]) {
q[i] <- q.dup
next
}
ind <- (1:(2*qd.hize))[p.wk<p[i]]
if (!length(ind)) {
wk <- mn+p[i]/(d.qd[1]*qd$wt[1])*gap[1]
}
else {
id.mx <- max(ind)
wk <- brk[id.mx+1]+(p[i]-p.wk[id.mx])/(d.qd[id.mx+1]*qd$wt[id.mx+1])*gap[id.mx+1]
}
q[i] <- q.dup <- wk
}
q[order.p]
}
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