Nothing
"densityCOPplot" <-
function(cop=NULL, para=NULL, deluv=0.002,
getmatrix=c("none", "cdenzz", "cden"), n=0,
ploton=TRUE, snv=TRUE, origins=TRUE,
contour.col=1, contour.lwd=1.5, ...) {
getmatrix <- match.arg(getmatrix)
U <- V <- seq(deluv, 1-deluv, by=+deluv)
nU <- length(U); nV <- length(V)
qU <- qnorm(U); qV <- qnorm(V)
cdenzz <- cden <- matrix(ncol=nU, nrow=nV)
ZV <- dnorm(qnorm(V))
for(i in 1:nU) {
uvals <- rep(U[i], nV)
dcop <- densityCOP(uvals, V, cop=cop, para=para, ...)
cden[,i] <- dcop
cdenzz[,i] <- dcop * dnorm(qnorm(uvals)) * ZV
}
rownames(cden) <- V; colnames(cden) <- U
rownames(cdenzz) <- V; colnames(cdenzz) <- U
if(ploton) {
if(snv) {
xlim <- ylim <- c(-1, 1)*rep(max(abs(range(c(qU, qV))), 2))
xlab <- "STANDARD NORMAL VARIATE OF U"
ylab <- "STANDARD NORMAL VARIATE OF V"
} else {
xlim <- ylim <- c(0, 1)
xlab <- "U, NONEXCEEDANCE PROBABILITY"
ylab <- "V, NONEXCEEDANCE PROBABILITY"
}
plot(xlim, ylim, type="n", xlim=xlim, ylim=ylim, xlab=xlab, ylab=ylab)
if(snv & origins) {
abline(h=0, lty=2)
abline(v=0, lty=2)
}
}
if(n > 0) {
UV <- simCOP(n=n, cop=cop, para=para, ploton=FALSE, points=TRUE, snv=snv,
pch=16, col=rgb(0, 0, 1, 0.3), cex=0.5, ...)
}
# The transposition t() is CRITICAL!!!!!!!! Let the 2nd example in
# densityCOPplot(), which is highly asymmetrical be the canonical demonstration.
if(snv) {
contour(x=qU, y=qV, z=t(cdenzz), lwd=contour.lwd, cex=2, add=TRUE, col=contour.col, ...)
} else {
contour(x=U, y=V, z=t(cdenzz), lwd=contour.lwd, cex=2, add=TRUE, col=contour.col, ...)
}
if(getmatrix == "cdenzz") {
return(cdenzz)
} else if(getmatrix == "cden") {
return(cden)
}
}
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