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Calculate per-point Hotelling statistic

Source: R/geom_hotelling.R
stat_outliers.Rd

Calculate per-point Hotelling statistic for use in ggplot

Usage

stat_outliers(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  type = c("t2data", "c2data"),
  level = 0.95,
  outlier_only = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

geom

The geometric object to use to display the data for this layer. When using a stat_*() function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following:

  • A Geom ggproto subclass, for example GeomPoint.

  • A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".

  • For more information and other ways to specify the geom, see the layer geom documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

  • The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

  • A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

  • For more information and other ways to specify the position, see the layer position documentation.

...

Additional parameters passed to underlying ggplot2::geom_polygon() or to ggplot2::layer().

type

t2data - Hotelling T2 data ellipse; t2mean - Hotelling confidence interval for the mean; c2data - normal data ellipse (using chi squared distribution).

level

Either coverage probability (for type = "t2data" or "c2data") or confidence level (for type = "t2mean").

outlier_only

Only return the statistic for outliers

na.rm

Logical. Should missing values be removed? Default is FALSE.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. annotation_borders().

Value

A stat layer that can be added to a ggplot object.

Details

This calculates the Hotelling statistic for each point in the plot, group-wise. This allows to use the statistics is_outlier, d2 (the squared Mahalanobis distance), c2crit (critical Chi-squared value for the specified level) and t2crit (critical Hotelling T2 value for the squared Mahalanobis distance) to be used as graphical parameters, e.g. for coloring the points (see Examples below) using the ggplot2::after_stat() function.

The is_outlier is simply either d2 > t2crit (if type="t2data" or type="t2mean") or d2 > c2crit (if type="c2data").

The type argument chooses between the regular Hotelling statistic (with type="t2data") or the Chi-squared statistic (with type="c2data"). The Hotelling statistic for the mean is not allowed as it makes no sense in the context of the outliers.

The function is a wrapper around the outliers() function, which does the actual calculations, and the parameters passed (level, type, robust) are passed on to that function. For example, to calculate robust statistic, use stat_outliers(robust=TRUE).

Examples

pca <- prcomp(iris[, 1:4], scale.=TRUE)
df <- cbind(iris, pca$x)

library(ggplot2)
ggplot(df, aes(PC1, PC2, group=Species)) +
  geom_hotelling(alpha=0.1, aes(fill = Species)) +
  scale_color_manual(values=c("TRUE"="red", "FALSE"="grey")) +
  stat_outliers(aes(color = after_stat(is_outlier)))


ggplot(df, aes(PC1, PC2, group=Species)) +
  geom_hotelling(alpha=0.1, level = .75, aes(fill = Species)) +
  stat_outliers(level = .75,
                        size=2,
                        aes(shape = Species,
                        color = after_stat(d2)))


# label the outliers
# note that you need to add the label aesthetics for the label geom to
# work
ggplot(df, aes(PC1, PC2, group=Species, label=rownames(df))) +
  geom_hotelling(level = 0.75, alpha=0.1, aes(fill = Species)) +
  geom_point(aes(color = Species)) +
  stat_outliers(level = .75, geom="label",
                        outlier_only = TRUE)