Confidence Ellipses

Plots confidence ellipses.

Usage

viz_confidence(x, ...)

wrap_confidence(x, ...)

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

# S4 method for class 'BootstrapCA'
viz_confidence(
  x,
  ...,
  margin = 1,
  axes = c(1, 2),
  level = 0.95,
  color = FALSE,
  fill = FALSE,
  symbol = FALSE
)

# S4 method for class 'PCOA'
viz_confidence(
  x,
  ...,
  axes = c(1, 2),
  group = NULL,
  level = 0.95,
  color = NULL,
  fill = FALSE,
  symbol = FALSE
)

# S4 method for class 'MultivariateAnalysis'
wrap_confidence(x, margin = 1, axes = c(1, 2), group = NULL, level = 0.95)

# S4 method for class 'PCOA'
wrap_confidence(x, axes = c(1, 2), group = NULL, level = 0.95)

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.

Value

wrap_confidence() returns a data.frame of envelope x and y coordinates. An extra column named group is added specifying the group an observation belongs to.

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

See also

Other envelopes: viz_ellipses(), viz_hull(), viz_tolerance()

Author

N. Frerebeau

Examples

## Load data
data("iris")

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

## Compute confidence ellipse coordinates
conf <- wrap_confidence(X, margin = 1, group = "Species", level = 0.95)

## Plot confidence ellipses
col <- c("#004488", "#DDAA33", "#BB5566")
viz_rows(X, extra_quali = iris$Species, color = col)
viz_confidence(X, group = iris$Species, color = col, level = 0.95)