From: Richard Yanicky <ryanicky_at_mindspring.com>

Date: Fri, 18 Jan 2008 11:25:22 -0500 (GMT-05:00)

Generalized Box Plots**ARGUMENTS:
**

...: vectors or a list containing a number of numeric compo-

pch: vector of plotting character for each group.

names.: names for each box (see argument names.' above). dnsty: a list with x' and y' components as output by density.

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Fri 18 Jan 2008 - 16:35:36 GMT

Date: Fri, 18 Jan 2008 11:25:22 -0500 (GMT-05:00)

David A James Phone: (908) 582-3082 Bell Labs, Lucent Technologies Fax: (908) 582-3340 600 Mountain Ave Email: dj at bell-labs.comMurray Hill, NJ 07974

Generalized Box Plots

**USAGE:
**

gboxplot(..., type = "box", range.=, width=, varwidth=F, notch=F, names.=, horiz = T, fill=F, col=1, old = T, plot.it=TRUE) gboxplot(..., type = "vase", from=, to=, kernel.width=, n=, width=, varwidth=F, notch=F, names.=, horiz = T, fill=F, col=1, plot.it=TRUE) gboxplot(..., type = "diamond", width=, varwidth=F, names.=, horiz = T, fill=F, col=1, pch, plot.it=TRUE) gboxplot(..., type = "pts", jitter.pts = F, width=, varwidth=F, notch=F, names.=, horiz = T, fill=F, col=1, pch, plot.it=TRUE)

...: vectors or a list containing a number of numeric compo-

nents (e.g., the output of split'). Missing values (NAs) are allowed. type=: character string (the first letter suffices) specifying type of gboxplots, currently "box" for Tukey's boxplots, "vase" for vase or violin plots (see Benjamini (1988) and Hintze and Nelson (1998)), "diamond" for diamond plots (see, for instance, JMP (1995)), or "pts" for one dimen- sional histograms (See Chambers et. al. (1983)). Type may also be the name of a user-written function that computes an object for which there exists a draw' method. For in- stance type = cmp.vase' specifies the function that com- putes vases and which returns an object of class "vase"; the method draw.vase' (automatically called by the generic draw') plots the vases. range.=: controls the strategy for the whiskers and the de- tached points beyond the whiskers. By default, whiskers are drawn to the nearest value not beyond a standard range from the quartiles; points beyond are drawn individually. Giving range.=0' forces whiskers to the full data range. Any positive value of range.' multiplies the standard range by this amount. The standard range is 1.5*(inter- quartile range). width=: vector of relative box widths. See also argument var- width'. varwidth=: if TRUE', box widths will be proportional to the square-root of the number of observations for the box. notch=: if TRUE', notched boxes are drawn, where non-overlap- ping of notches of boxes indicates a difference at a rough 5% significance level. names.=: optional character vector of names for the groups. If omitted, names used in labeling the plot will be taken from the names of the arguments and from the names at- tribute of lists. plot.it=: if TRUE', the box plot will be produced; otherwise, the calculated summaries of the arguments are returned. old=: if TRUE', the plot will be produced in the style de- scribed in the Tukey (1977) reference; otherwise, the plot will follow the more modern style introduced in Tukey (1990), where the advantages of the new style are de- scribed. horiz=: if TRUE boxes are drawn horizontally. from: (vaseplots) lower bound for the percent of data to use in fitting density'. By default 0.25. to: (vaseplots) upper bound for the percent of data to use in fitting density'. By default 0.75. kernel.width: (vaseplots) width of the kernel window, as de- fined in the function density'. Its default corresponds to the width of a histogram bar as computed by Doane's rule. n: (vaseplot) number of equally spaced density estimates. De- fault is 25. jitter.pts: (pts) if logical, it specifies whether or not to jitter the points inside each group. If numeric it speci- fies the amount, in data units, to jitter. Default is FALSE. fill: should boxes or vases be filled? Default is FALSE.col: vector of colors for each group.

pch: vector of plotting character for each group.

Graphical parameters may also be supplied as arguments to this function (see par) VALUE: If plot.it' is FALSE', the value is a list as long as there are data vectors with the components listed below. Otherwise the generic function draw' is invoked with these components, plus optional width', varwidth' and notch', to produce the plot. Note that draw' returns a list of box/vase centers. stats: vector giving the upper extreme, upper quartile, medi- an, lower quartile, and lower extreme for each box. n: the number of observations in each group. conf: vector giving confidence limits for the median.out: vector of outlying points.

names.: names for each box (see argument names.' above). dnsty: a list with x' and y' components as output by density.

**NOTES:
**

In the case of vase plots, the density is estimated using kernel smoothing --- this was done for expediency, but other density estimates may be easily added (e.g., local polynomial fitting as in Loader (1996)). Also note that the aspect ratio of the density traces may be such that it distorts important features of the data. REFERENCE: Tukey, John W., Exploratory Data Analysis, Addison-Wesley, Reading, Mass., 1977. Tukey, John W., "Data Based Graphics: Visual Display in the Decades to Come", Statistical Science, pp. 327-339, 1990. Benjamini, Yoav "Opening the Box of a Boxplot" The Ameri- can Statistician, pp. 257-262, 1988. Chamber, J. M., Cleveland, W. S., Klein, P., and Tukey, P. A. Graphical Methods for Data Analysis, Wadsworth, Pacif- ic Grove, CA., 1983. Hintze, Jerry L., and Nelson, Ray D., "Violin Plots: A Box Plot-Density Trace Synergism", The American Statistician, pp. 181-184, 1998. Loader, Clive, "Local Likelihood Density Estimation", An- nals of Statistics, 1996. "JMP User's Guide", SAS Institute Inc., 1995. EXAMPLES: gboxplot(group1,group2,group3) gboxplot(split(salary,age),varwidth=TRUE,notch=TRUE) # the example plot is produced by: gboxplot( split(lottery.payoff,lottery.number%/%100), main=lottery.label, sub="Leading Digit of Winning Numbers", ylab="Payoff") gboxplot( split(Mileage, Type), type = "vase", col=1:6) gboxplot( split(Mileage, Type), type = "pts", jitter=3, col=1:6)

Thank You,

Richard

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