stat_cone | R Documentation |
This stat layer restricts a dataset with x
and y
variables
to the points that lie on its conical hull (other than the origin).
stat_cone( mapping = NULL, data = NULL, geom = "path", position = "identity", origin = FALSE, show.legend = NA, inherit.aes = TRUE, ... )
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
geom |
The geometric object to use to display the data, either as a
|
position |
Position adjustment, either as a string naming the adjustment
(e.g. |
origin |
Logical; whether to include the origin with the transformed
data. Defaults to |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
... |
Additional arguments passed to |
A ggproto layer.
ggbiplot()
uses ggplot2::fortify()
internally to produce a single data
frame with a .matrix
column distinguishing the subjects ("rows"
) and
variables ("cols"
). The stat layers stat_rows()
and stat_cols()
simply
filter the data frame to one of these two.
The geom layers geom_rows_*()
and geom_cols_*()
call the corresponding
stat in order to render plot elements for the corresponding factor matrix.
geom_dims_*()
selects a default matrix based on common practice, e.g.
points for rows and arrows for columns.
The convenience function ord_aes()
can be used to incorporate all
coordinates of the ordination model into a statistical transformation. It
maps the coordinates to the custom aesthetics ..coord1
, ..coord2
, etc.
Some transformations, e.g. stat_center()
, are commutative with projection
to the 'x' and 'y' coordinates. If they detect aesthetics of the form
..coord[0-9]+
, then ..coord1
and ..coord2
are converted to x
and y
while any remaining are ignored.
Other transformations, e.g. stat_spantree()
, yield different results in a
planar biplot when they are computer before or after projection. If such a
stat layer detects these aesthetics, then the lot of them are used in the
transformation.
In either case, the stat layer returns a data frame with position aesthetics
x
and y
.
Other stat layers:
stat_center()
,
stat_chull()
,
stat_scale()
,
stat_spantree()
# centered principal components analysis of U.S. personal expenditure data USPersonalExpenditure %>% prcomp() %>% as_tbl_ord() %>% augment_ord() %>% # allow radiating text to exceed plotting window ggbiplot(aes(label = name), clip = "off", sec.axes = "cols", scale.factor = 50) + geom_rows_label(size = 3) + geom_cols_vector() + # omit labels in the conical hull without the origin stat_cols_cone(linetype = "dotted") + geom_cols_text_radiate(stat = "cone") + ggtitle( "U.S. Personal Expenditure data, 1940-1960", "Row-principal biplot of centered PCA" )
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