sieve {vcd} | R Documentation |
(Extended) sieve displays for n-way contingency tables: plots rectangles with areas proportional to the expected cell frequencies and filled with a number of squares equal to the observed frequencies. Thus, the densities visualize the deviations of the observed from the expected values.
## Default S3 method: sieve(x, condvars = NULL, gp = NULL, shade = NULL, legend = FALSE, split_vertical = NULL, direction = NULL, spacing = NULL, spacing_args = list(), sievetype = c("observed","expected"), main = NULL, sub = NULL, ...) ## S3 method for class 'formula': sieve(formula, data, ..., main = NULL, sub = NULL, subset = NULL)
x |
a contingency table in array form, with optional category
labels specified in the dimnames(x) attribute. |
condvars |
vector of integers or character strings indicating conditioning variables, if any. The table will be permuted to order them first. |
formula |
a formula specifying the variables used to create a
contingency table from data . For convenience, conditioning
formulas can be specified; the conditioning variables will then be
used first for splitting. Formulas for sieve displays (unlike
those for doubledecker plots) have no response variable. |
data |
either a data frame, or an object of class "table"
or "ftable" . |
subset |
an optional vector specifying a subset of observations to be used. |
shade |
logical specifying whether gp should be used or not
(see gp ). If TRUE and expected is unspecified,
a default model is fitted: if condvars is specified, a
corresponding conditional independence model, and else the total
independence model. If shade is NULL (default),
gp is used if specified. |
sievetype |
logical indicating whether rectangles should be filled
according to observed or expected frequencies. |
gp |
object of class "gpar" , shading function or a
corresponding generating function (see details of strucplot and
shadings ). Components of "gpar"
objects are recycled as needed along the last splitting
dimension. The default is a modified version of
shading_Friendly :
if sievetype is "observed" , cells with positive
residuals are painted red, and cells with negative residuals
blue. If sievetype is "expected" , the sieves' color is
gray. Ignored if shade = FALSE . |
legend |
either a legend-generating function, a legend
function (see details of strucplot and
legends ), or a logical value.
If legend is NULL or TRUE and gp is a
function, legend defaults to legend_resbased . |
split_vertical |
vector of logicals of length k, where k
is the number of margins of x (default: FALSE ).
Values are recycled as needed.
A TRUE component indicates that the tile(s) of the
corresponding dimension should be split vertically, FALSE
means horizontal splits.
Ignored if direction is not NULL . |
direction |
character vector of length k, where k is the
number of margins of x (values are recycled as needed).
For each component, a value of "h" indicates that the tile(s)
of the corresponding dimension should be split horizontally, whereas
"v" indicates vertical split(s). |
spacing |
spacing object, spacing function, or corresponding
generating function (see strucplot for more
information).
The default is no spacing at all if x has two dimensions,
and spacing_increase for more dimensions. |
spacing_args |
list of arguments for the generating function, if
specified (see strucplot for more information). |
main, sub |
either a logical, or a character string used for plotting
the main (sub) title. If logical and TRUE , the
name of the data object is used. |
... |
Other arguments passed to strucplot |
sieve
is a generic function which currently has a default method and a
formula interface. Both are high-level interfaces to the
strucplot
function, and produce (extended) sieve
displays. Most of the functionality is described there, such as
specification of the independence model, labeling, legend, spacing,
shading, and other graphical parameters.
The layout is very flexible: the specification of shading, labeling,
spacing, and legend is modularized (see strucplot
for
details).
The "structable"
visualized is returned invisibly.
To be faithful to the original definition by Riedwyl & Schüpbach, the default is to have no spacing between the tiles for two-way tables.
David Meyer David.Meyer@R-project.org
H. Riedwyl & M. Schüpbach (1994), Parquet diagram to plot contingency tables. In F. Faulbaum (ed.), Softstat '93: Advances in Statistical Software, 293–299. Gustav Fischer, New York.
M. Friendly (2000), Visualizing Categorical Data, SAS Institute, Cary, NC.
David Meyer, Achim Zeileis, and Kurt Hornik (2006).
The strucplot framework: Visualizing multi-way contingency tables with
vcd.
Journal of Statistical Software, 17(3), 1-48.
URL http://www.jstatsoft.org/v17/i03/ and available as
vignette("strucplot")
.
assoc
,
strucplot
,
mosaic
,
structable
,
doubledecker
data("HairEyeColor") ## aggregate over 'sex': (tab <- margin.table(HairEyeColor, c(2,1))) ## plot expected values: sieve(tab, sievetype = "expected", shade = TRUE) ## plot observed table: sieve(tab, shade = TRUE) ## plot complete diagram: sieve(HairEyeColor, shade = TRUE) ## an example for the formula interface: data("VisualAcuity") sieve(Freq ~ right + left, data = VisualAcuity) ## example with observed values in the cells: sieve(Titanic, pop = FALSE, shade = TRUE) labeling_cells(text = Titanic, gp_text = gpar(fontface = 2))(Titanic)