mosaicplot {base} | R Documentation |
Plots a mosaic on the current graphics device.
mosaicplot(x, ...) mosaicplot(X, main = NULL, xlab = NULL, ylab = NULL, sort = NULL, off = NULL, dir = NULL, color = FALSE, shade = FALSE, margin = NULL, type = c("pearson", "deviance", "FT")) mosaicplot(formula, data = NULL, ..., subset, na.action)
x |
an R object. |
X |
a contingency table in array form, with optional category
labels specified in the dimnames(x) attribute. The table is
best created by the table() command. |
main |
character string for the mosaic title. |
xlab,ylab |
x- and y-axis labels used for the plot; by default,
the first and second element of names(dimnames(X)) (i.e., the
name of the first and second variable in X ). |
sort |
vector ordering of the variables, containing a permutation
of the integers 1:length(dim(x)) (the default). |
off |
vector of offsets to determine percentage spacing at each level of the mosaic (appropriate values are between 0 and 20, and the default is 10 at each level). There should be one offset for each dimension of the contingency table. |
dir |
vector of split directions ("v" for vertical and
"h" for horizontal) for each level of the mosaic, one
direction for each dimension of the contingency table. The
default consists of alternating directions, beginning with a
vertical split. |
color |
(TRUE or vector of integer colors) for color
shading or (FALSE , the default) for empty boxes with no
shading. Ignored if shade is not FALSE . |
shade |
a logical indicating whether to produce extended mosaic
plots, or a numeric vector of at most 5 distinct positive numbers
giving the absolute values of the cut points for the residuals. By
default, shade is FALSE , and simple mosaics are
created. Using shade = TRUE cuts absolute values at 2 and
4. |
margin |
a list of vectors with the marginal totals to be fit in
the log-linear model. By default, an independence model is fitted.
See loglin for further information. |
type |
a character string indicating the type of residual to be
represented. Must be one of "pearson" (giving components of
Pearson's chi-squared), "deviance" (giving
components of the likelihood ratio chi-squared), or
"FT" for the Freeman-Tukey residuals. The value of this
argument can be abbreviated. |
formula |
a formula, such as y ~ x . |
data |
a data.frame (or list) from which the variables in
formula should be taken. |
... |
further arguments to the default mosaicplot method. |
subset |
an optional vector specifying a subset of observations to be used for plotting. |
na.action |
deprecated. |
This is a generic function. It currently has a default method
(mosaicplot.default
) and a formula interface
(mosaicplot.formula
).
Extended mosaic displays show the standardized residuals of a loglinear model of the counts from by the color and outline of the mosaic's tiles. (Standardized residuals are often referred to a standard normal distribution.) Negative residuals are drawn in shaded of red and with broken outlines; positive ones are drawn in blue with solid outlines.
See Emerson (1998) for more information and a case study with television viewer data from Nielsen Media Research.
S-PLUS original by John Emerson emerson@stat.yale.edu. Modified and enhanced for R by KH.
Hartigan, J.A., and Kleiner, B. (1984) A mosaic of television ratings. The American Statistician, 38, 3235.
Emerson, J. W. (1998) Mosaic displays in S-PLUS: a general implementation and a case study. Statistical Computing and Graphics Newsletter (ASA), 9, 1, 1723.
Friendly, M. (1994) Mosaic displays for multi-way contingency tables. Journal of the American Statistical Association, 89, 190200.
The home page of Michael Friendly (http://hotspur.psych.yorku.ca/SCS/friendly.html) provides information on various aspects of graphical methods for analyzing categorical data, including mosaic plots.
data(Titanic) mosaicplot(Titanic, main = "Survival on the Titanic", color = TRUE) data(HairEyeColor) mosaicplot(HairEyeColor, shade = TRUE) ## Independence model of hair and eye color and sex. Indicates that ## there are significantly more blue eyed blond females than expected ## in the case of independence (and too few brown eyed blond females). mosaicplot(HairEyeColor, shade = TRUE, margin = list(c(1,2), 3)) ## Model of joint independence of sex from hair and eye color. Males ## are underrepresented among people with brown hair and eyes, and are ## overrepresented among people with brown hair and blue eyes, but not ## ``significantly''. ## Formula interface: visualize crosstabulation of numbers of gears and ## carburettors in Motor Trend car data. data(mtcars) mosaicplot(~ gear + carb, data = mtcars, color = TRUE)