true.theta <- theta
true.val <- c(true.theta, nlogl.GIG.(true.theta, u=U)) # theoretical optimum
opt <- ml@coef # optimizer-optimum
opt.val <- c(opt, nlogl.GIG.(opt, u=U)) # optimizer-optimum and its value
pts <- rbind(true.val, opt.val) # points to add to wireframe plot
title <- "-log-likelihood of an Archimedean GIG copula" # title
sub <- substitute(italic(n) == N ~~~ italic(d)== D ~~~
tau == TAU ~~~ "#{eval}:" ~ NIT,
list(N=n, D=d, TAU= tau, NIT= ml@details$counts[[1]]))
sub <- as.expression(sub) # lattice bug
wireframe(val.grid ~ grid[,1] * grid[,2], screen=list(z=70, x=-55), zoom=0.95,
xlab = expression(italic(theta)), ylab = expression(italic(beta)),
zlab = list(as.expression(-log~L * group("(",list(theta,beta),")")), rot=90),
main=title, sub=sub, pts=pts, scales=list(col=1, arrows=FALSE),
par.settings=list(axis.line=list(col="transparent"),
clip=list(panel="off")), zlim=c(min(val.grid, pts[,3]),
max(val.grid, pts[,3])), aspect=1,
panel.3d.wireframe = function(x,y,z,xlim,ylim,zlim,xlim.scaled,
ylim.scaled,zlim.scaled,pts,...) {
panel.3dwire(x=x, y=y, z=z, xlim=xlim, ylim=ylim, zlim=zlim,
xlim.scaled=xlim.scaled, ylim.scaled=ylim.scaled,
zlim.scaled=zlim.scaled, alpha.regions=0.8, ...)
panel.3dscatter(x=pts[,1], y=pts[,2], z=pts[,3],
xlim=xlim, ylim=ylim, zlim=zlim,
xlim.scaled=xlim.scaled, ylim.scaled=ylim.scaled,
zlim.scaled=zlim.scaled, type="p", col=c("red","blue"),
pch=c(3,4), lex=2, cex=1.4, .scale=TRUE, ...)
},
key = list(x=0.64, y=1.01,
points = list(pch=c(3,4), col=c("red","blue"), lwd=2, cex=1.4),
text = list(c("True value", "Optimum of optimizer")), padding.text=3,
cex=1, align=TRUE, transparent=TRUE))RetroSearch is an open source project built by @garambo | Open a GitHub Issue
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