dimensio (version 0.10.1)

viz_wrap: Plot Envelopes

Description

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,
  color = NULL,
  fill = FALSE,
  symbol = FALSE
)
# S4 method for BootstrapCA
viz_tolerance(
  x,
  ...,
  margin = 1,
  axes = c(1, 2),
  level = 0.95,
  color = FALSE,
  fill = FALSE,
  symbol = FALSE
)
# S4 method for MultivariateAnalysis
viz_confidence(
  x,
  ...,
  margin = 1,
  axes = c(1, 2),
  group = NULL,
  level = 0.95,
  color = NULL,
  fill = FALSE,
  symbol = FALSE
)
# S4 method for BootstrapCA
viz_confidence(
  x,
  ...,
  margin = 1,
  axes = c(1, 2),
  level = 0.95,
  color = FALSE,
  fill = FALSE,
  symbol = FALSE
)
# S4 method for MultivariateAnalysis
viz_hull(
  x,
  ...,
  margin = 1,
  axes = c(1, 2),
  group = NULL,
  color = NULL,
  fill = FALSE,
  symbol = FALSE
)
# S4 method for BootstrapCA
viz_hull(
  x,
  ...,
  margin = 1,
  axes = c(1, 2),
  color = FALSE,
  fill = FALSE,
  symbol = FALSE
)

Value

viz_*()is called for its side-effects: it results in a graphic being displayed. Invisibly returns x.

Arguments

x

An object from which to wrap observations (a CA, MCA or PCA 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 for which to compute results.

group

A vector specifying the group an observation belongs to.

level

A numeric vector specifying the confidence/tolerance level.

color

The colors for borders (will be mapped to group). Ignored if set to FALSE. If NULL, the default color scheme will be used.

fill

The background colors (will be mapped to group). Ignored if set to FALSE.

symbol

A vector of symbols (will be mapped to group). Ignored if set to FALSE.

Author

N. Frerebeau

See Also

Other plot methods: biplot(), plot(), screeplot(), viz_contributions(), viz_individuals(), viz_variables(), wrap

Examples

## Load data
data("iris")

## Compute principal components analysis
X <- pca(iris, scale = TRUE, sup_quali = "Species")

## Plot with convex hulls
col <- c("#004488", "#DDAA33", "#BB5566")
viz_rows(X, extra_quali = iris$Species, color = col)
viz_hull(X, group = iris$Species, color = col)

## Plot with tolerance ellipses
col <- c("#004488", "#DDAA33", "#BB5566")
viz_rows(X, extra_quali = iris$Species, color = col)
viz_tolerance(X, group = iris$Species, color = col)