Wednesday, August 22, 2007


amusing comment on colour manager

> ## Truly awful colour scheme to illustrate flexibility

> plot(e, colors=meta.colors(summary="green",lines=c("purple","skyblue"),
+ box="red",zero="yellow",text=palette(),background="tomato",
+ axes="lightgreen"))

metaplot -
Plot confidence intervals with boxes indicating the sample size/precision and optionally a diamond indicating a summary confidence interval. This function is usually called by plot methods for meta-analysis objects.


plot normal curve

panelbbplot from Hmisc

For all their good points, box plots have a high ink/information ratio in that they mainly display 3 quartiles. Many practitioners have found that the "outer values" are difficult to explain to non-statisticians and many feel that the notion of "outliers" is too dependent on (false) expectations that data distributions should be Gaussian.

panel.bpplot is a panel function for use with trellis, especially for bwplot. It draws box plots (without the whiskers) with any number of user-specified "corners" (corresponding to different quantiles), but it also draws box-percentile plots similar to those drawn by Jeffrey Banfield's ( bpplot function. To quote from Banfield, "box-percentile plots supply more information about the univariate distributions. At any height the width of the irregular 'box' is proportional to the percentile of that height, up to the 50th percentile, and above the 50th percentile the width is proportional to 100 minus the percentile. Thus, the width at any given height is proportional to the percent of observations that are more extreme in that direction. As in boxplots, the median, 25th and 75th percentiles are marked with line segments across the box."

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