On May 9, 2011, at 12:35 AM, Deepayan Sarkar wrote:
On Mon, May 9, 2011 at 2:20 AM, Thomas Lumley <tlum...@uw.edu> wrote:
On Mon, May 9, 2011 at 6:35 AM, Deepayan Sarkar
<deepayan.sar...@gmail.com> wrote:
On Sat, May 7, 2011 at 1:55 AM, Raphael Mazor
<rapha...@sccwrp.org> wrote:
Is it possible to create weighted boxplots or violin plots in
lattice?
It seems that you can specify weights for panel.histogram() and
panel.densityplot(), but not for panel.bwplot or panel.violin().
Not for panel.histogram() either.
It's not immediately obvious how you would get weighted boxplots.
The way the survey world does it is to get weighted quantiles and
work
from them, as in survey:::svyboxplot(). The only tricky decision is
what to do with outliers, since I haven't been able to think of any
good way of indicating weights on them.
So I guess with bwplot() one would have to write a version of
boxplot.stats() that uses weighted quantiles, and then write a
modified panel function.
A crude approximation (if the weights don't vary too much) may be to
scale and round the weights to integers, and then repeat each data
point; e.g., newx <- rep(x, w), etc.
You could do a bit better if you just substituted wtd.quantile from
Hmisc with an x and weights argument for the fivenum call in
boxplot.stats.
require(Hmisc)
> ?wtd.quantile
> fivenum(x=1:10)
[1] 1.0 3.0 5.5 8.0 10.0
> wtd.quantile(x=1:10)
0% 25% 50% 75% 100%
1.00 3.25 5.50 7.75 10.00
> wtd.quantile( x = 1:10, weights = 1:10)
0% 25% 50% 75% 100%
1 5 7 9 10
(Most people think the hinges are at the 25th and 75th percentiles
anyway.)
-Deepayan
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