shadings {vcd} | R Documentation |
Shading-generating functions for computing residual-based shadings for mosaic and association plots.
shading_hcl(observed, residuals = NULL, expected = NULL, df = NULL, h = NULL, c = NULL, l = NULL, interpolate = c(2, 4), lty = 1, p.value = NULL, level = 0.95, ...) shading_hsv(observed, residuals = NULL, expected = NULL, df = NULL, h = c(2/3, 0), s = c(1, 0), v = c(1, 0.5), interpolate = c(2, 4), lty = 1, p.value = NULL, level = 0.95, ...) shading_max(observed = NULL, residuals = NULL, expected = NULL, df = NULL, h = NULL, c = NULL, l = NULL, lty = 1, level = c(0.9, 0.99), n = 1000, ...) shading_Friendly(observed = NULL, residuals = NULL, expected = NULL, df = NULL, h = c(2/3, 0), lty = 1:2, interpolate = c(2, 4), ...) shading_binary(observed = NULL, residuals = NULL, expected = NULL, df = NULL, col = hcl(c(260, 0), 50, 70))
observed |
contingecy table of observed values |
residuals |
contingecy table of residuals |
expected |
contingecy table of expected values |
df |
degrees of freedom of the associated independence model. |
h |
hue value in the HCL or HSV color description, has to be
in [0, 360] for HCL and in [0, 1] for HSV colors. The default is
to use blue and red for positive and negative residuals respectively.
In the HCL specification it is c(260, 0) by default and for HSV
c(2/3, 0) . |
c |
chroma value in the HCL color description. Defaults to c(100, 20)
for significant and non-significant results respectively. |
l |
luminance value in the HCL color description. Defaults to c(90, 50)
for small and large residuals respectively. |
s |
saturation value in the HSV color description. Defaults to c(1, 0)
for large and small residuals respectively. |
v |
saturation value in the HSV color description. Defaults to c(1, 0.5)
for significant and non-significant results respectively. |
interpolate |
a specification for mapping the absolute size of the residuals to a value in [0, 1]. This can be either a function or a numeric vector. In the latter case, a step function with steps of equal size going from 0 to 1 is used. |
lty |
a vector of two line types for positive and negative residuals respectively. Recycled if necessary. |
p.value |
the p value associated with the independence model. By default,
this is computed from a Chi-squared distribution with df degrees of freedom. |
level |
confidence level of the test used. If p.value is smaller than
1 - level , bright colors are used, otherwise dark colors are employed. For
shading_max a vector of levels can be supplied. The corresponding critical
values are then used as interpolate cut-offs. |
n |
number of permutations used in the call to coindep_test . |
col |
a vector of two colors for positive and negative residuals respectively. |
... |
Other arguments passed to hcl
or hsv , respectively. |
These shading-generating functions can be passed to strucplot
to generate
residual-based shadings for contingency tables. strucplot
calls these
functions with the arguments observed
, residuals
, expected
,
df
which give the observed values, residuals, expected values and associated
degrees of freedom for a particular contingency table and associated independence
model.
The shadings shading_hcl
and shading_hsv
do the same thing conceptually,
but use HCL or HSV colors respectively. The former is usually preferred because they
are perceptually uniform. Both shadings visualize the sign of the residuals of
an independence model using two hues (by default: blue and red). The absolute size of
the residuals is visualized by the colorfulness, by default in three categories:
very colorful for large residuals (> 4), less colorful for medium sized residuals (< 4 and > 2),
grey/white for small residuals (< 2). More categories or a continuous scale can
be specified by setting interpolate
. Furthermore, the result of a significance
test can be visualized by the amount of grey in the colors. If significant, bright
colors are used, if not, darker colors with a higher amount of grey are used.
The shading shading_max
is applicable in 2-way contingency tables and uses
a similar strategy as shading_hcl
. But instead of using the cut-offs 2 and 4,
it employs the critical values for the maximum statistic (by default at 90% and 99%).
Consequently, color in the plot signals a significant result at 90% or 99% significance
level, respectively. The test is carried out by calling coindep_test
.
The shading shading_Friendly
is very similar to shading_hsv
, but additionally
codes the sign of the residuals by different line types.
The shading shading_binary
just visualizes the sign of the residuals by using
two different colors.
A shading function which takes only a single argument, interpreted as a
vector/table of residuals, and returns a "gpar"
object with the
corresponding vector(s)/table(s) of graphical parameter(s).
Achim Zeileis Achim.Zeileis@R-project.org
hcl
,
hsv
,
mosaic
,
assoc
,
strucplot
## load Arthritis data data(Arthritis) art <- xtabs(~Treatment + Improved, data = Arthritis) ## plain mosaic display without shading mosaic(art) ## with shading for independence model mosaic(art, shade = TRUE) ## which uses the HCL shading mosaic(art, gp = shading_hcl) ## the residuals are two small to have color, ## hence the cut-offs can be modified mosaic(art, gp = shading_hcl, gp_args = list(interpolate = c(1, 1.8))) ## the same with the Friendly palette ## (without significance testing) mosaic(art, gp = shading_Friendly, gp_args = list(interpolate = c(1, 1.8))) ## assess independence using the maximum statistic ## cut-offs are now critical values for the test statistic mosaic(art, gp = shading_max) ## association plot with shading as in base R assoc(art, gp = shading_binary(col = c(1, 2)))