xyplot()
draws “zeta diagrams”, also visualizing
confidence intervals and their asymmetry. densityplot()
draws the profile densities. splom()
draws profile pairs plots. Contours are for the
marginal two-dimensional regions (i.e. using df = 2).# S3 method for thpr
xyplot(x, data = NULL,
levels = sqrt(qchisq(pmax.int(0, pmin.int(1, conf)), df = 1)),
conf = c(50, 80, 90, 95, 99)/100,
absVal = FALSE, scales=NULL,
which = 1:nptot, …)# S3 method for thpr
densityplot(x, data, …)
# S3 method for thpr
splom(x, data,
levels = sqrt(qchisq(pmax.int(0, pmin.int(1, conf)), 2)),
conf = c(50, 80, 90, 95, 99)/100, which = 1:nptot,
draw.lower = TRUE, draw.upper = TRUE, …)
conf
.abs(.)
olute values
should be plotted, often preferred for confidence interval
visualization.xyplot
profile-methods
for details).xyplot
,
densityplot
, or splom
from package
lattice, respectively."trellis"
object (lattice package)
which when print()
ed produces plots on the current
graphic device."trellis"
object, see above."trellis"
object, see above.profile
, notably for an
example.## see example("profile.merMod")
Run the code above in your browser using DataLab