spineplot {graphics} | R Documentation

## Spine Plots and Spinograms

### Description

Spine plots are a special cases of mosaic plots, and can be seen as a generalization of stacked (or highlighted) bar plots. Analogously, spinograms are an extension of histograms.

### Usage

    spineplot(x, ...)

    ## Default S3 method:
    spineplot(x, y = NULL,
              breaks = NULL, tol.ylab = 0.05, off = NULL,
              col = NULL, main = "", xlab = NULL, ylab = NULL,
              xaxlabels = NULL, yaxlabels = NULL,
              xlim = NULL, ylim = c(0, 1), ...)

    ## S3 method for class 'formula':
    spineplot(formula, data = list(),
              breaks = NULL, tol.ylab = 0.05, off = NULL,
              col = NULL, main = "", xlab = NULL, ylab = NULL,
              xaxlabels = NULL, yaxlabels = NULL,
              xlim = NULL, ylim = c(0, 1), ...,
              subset = NULL)

### Arguments

`x` | an object, the default method expects either a single variable (interpreted to be the explanatory variable) or a 2-way table. See details.
`y` | a `"factor"` interpreted to be the dependent variable
`formula` | a `"formula"` of type `y ~ x` with a single dependent `"factor"` and a single explanatory variable.
`data` | an optional data frame.
`breaks` | if the explantory variable is numeric, this controls how it is discretized. `breaks` is passed to `hist` and can be a list of arguments.
`tol.ylab` | convenience tolerance parameter for y-axis annotation. If the distance between two labels drops under this threshold, they are plotted equidistantly.
`off` | vertical offset between the bars (in per cent). It is fixed to `0` for spinograms and defaults to `2` for spine plots.
`col` | a vector of fill colors of the same length as `levels(y)`. The default is to call `gray.colors`.
`main, xlab, ylab` | character strings for annotation
`xaxlabels, yaxlabels` | character vectors for annotation of x and y axis. Default to `levels(y)` and `levels(x)`, respectively for the spine plot. For `xaxlabels` in the spinogram, the breaks are used.
`xlim, ylim` | the range of x and y values with sensible defaults.
`...` | additional arguments passed to `rect`.
`subset` | an optional vector specifying a subset of observations to be used for plotting.

### Details

`spineplot` creates either a spinogram or a spine plot. It can be called via `spineplot(x, y)` or `spineplot(y ~ x)` where `y` is interpreted to be the dependent variable (and has to be categorical) and `x` the explanatory variable. `x` can be either categorical (then a spine plot is created) or numerical (then a spinogram is plotted). Additionally, `spineplot` can also be called with only a single argument which then has to be a 2-way table, interpreted to correspond to `table(x, y)`.

Both, spine plots and spinograms, are essentially mosaic plots with special formatting of spacing and shading. Conceptually, they plot P(y | x) against P(x). For the spine plot (where both x and y are categorical), both quantities are approximated by the corresponding empirical relative frequencies. For the spinogram (where x is numerical), x is first discretized (by caling `hist` with `breaks` argument) and then empirical relative frequencies are taken.

Thus, spine plots can also be seen as a generalization of stacked bar plots where not the heights but the widths of the bars corresponds to the relative frequencies of `x`. The heights of the bars then correspond to the conditional relative frequencies of `y` in every `x` group. Analogously, spinograms extend stacked histograms.

### Value

The table visualized is returned invisibly.

### Author(s)

Achim Zeileis Achim.Zeileis@R-project.org

### References

Friendly, M. (1994), Mosaic displays for multi-way contingency tables. Journal of the American Statistical Association, 89, 190–200.

Hartigan, J.A., and Kleiner, B. (1984), A mosaic of television ratings. The American Statistician, 38, 32–35.

Hofmann, H., Theus, M. (2005), Interactive graphics for visualizing conditional distributions, Unpublished Manuscript.

Hummel, J. (1996), Linked bar charts: Analysing categorical data graphically. Computational Statistics, 11, 23–33.

### See Also

`mosaicplot`, `hist`, `cdplot`

### Examples

    ## treatment and improvement of patients with rheumatoid arthritis
    treatment <- factor(rep(c(1, 2), c(43, 41)), levels = c(1, 2),
                        labels = c("placebo", "treated"))
    improved <- factor(rep(c(1, 2, 3, 1, 2, 3), c(29, 7, 7, 13, 7, 21)),
                       levels = c(1, 2, 3), labels = c("none", "some", "marked"))

    ## (dependence on a categorical variable)
    (spineplot(improved ~ treatment))

    ## applications and admissions by department at UC Berkeley
    ## (two-way tables)
    (spineplot(margin.table(UCBAdmissions, c(3, 2)),
               main = "Applications at UCB"))
    (spineplot(margin.table(UCBAdmissions, c(3, 1)),
               main = "Admissions at UCB"))

    ## NASA space shuttle o-ring failures
    fail <- factor(c(2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1,
                     1, 1, 1, 2, 1, 1, 1, 1, 1),
                   levels = c(1, 2), labels = c("no", "yes"))
    temperature <- c(53, 57, 58, 63, 66, 67, 67, 67, 68, 69, 70, 70,
                     70, 70, 72, 73, 75, 75, 76, 76, 78, 79, 81)

    ## (dependence on a numerical variable)
    (spineplot(fail ~ temperature))
    (spineplot(fail ~ temperature, breaks = 3))
    (spineplot(fail ~ temperature, breaks = quantile(temperature)))

[Package graphics version 2.3.1 Index]