Plot Envelopes
Usage
viz_hull(x, ...)
viz_confidence(x, ...)
viz_tolerance(x, ...)
# S4 method for MultivariateAnalysis
viz_tolerance(x, margin = 1, axes = c(1, 2), group = NULL, level = 0.95, ...)
# S4 method for BootstrapCA
viz_tolerance(x, margin = 1, axes = c(1, 2), level = 0.95, ...)
# S4 method for MultivariateAnalysis
viz_confidence(x, margin = 1, axes = c(1, 2), group = NULL, level = 0.95, ...)
# S4 method for BootstrapCA
viz_confidence(x, margin = 1, axes = c(1, 2), level = 0.95, ...)
# S4 method for MultivariateAnalysis
viz_hull(x, margin = 1, axes = c(1, 2), group = NULL, ...)
# S4 method for BootstrapCA
viz_hull(x, margin = 1, axes = c(1, 2), ...)
Arguments
- x
An object from which to wrap observations (a
CA
orPCA
object).- ...
Further graphical parameters to be passed to
graphics::polygon()
.- margin
A length-one
numeric
vector giving the subscript which the data will be returned:1
indicates individuals/rows (the default),2
indicates variables/columns.- axes
A length-two
numeric
vector giving the dimensions to be for which to compute results.- group
A vector specifying the group an observation belongs to.
- level
A
numeric
vector specifying the confidence/tolerance level.
Value
viz_*()
is called for its side-effects: it results in a graphic being
displayed. Invisibly returns x
.
See also
Other plot methods:
biplot()
,
screeplot()
,
viz_contributions()
,
viz_individuals()
,
viz_variables()
,
wrap
Examples
## Load data
data("iris")
## Compute principal components analysis
X <- pca(iris, scale = TRUE)
#> 1 qualitative variable was removed: Species.
## Convex hull coordinates
hulls <- wrap_hull(X, margin = 1, group = iris$Species)
## Confidence ellipse coordinates
conf <- wrap_confidence(X, margin = 1, group = iris$Species,
level = c(0.68, 0.95))
## Tolerance ellipse coordinates
conf <- wrap_confidence(X, margin = 1, group = iris$Species, level = 0.95)
## Plot with convex hulls
col <- c("#004488", "#DDAA33", "#BB5566")
viz_rows(X, highlight = iris$Species, col = col)
viz_hull(X, group = iris$Species, border = col)