ggplot stat_summary(mean_cl_boot)

Ben Bolker · 2011-11-09T21:30:02Z

David Winsemius comcast.net> writes: > On Nov 9, 2011, at 2:59 PM, Nathan Miller wrote: > > > Hello, > > > > This is a pretty simple question, but after spending quite a bit of > > time > > looking at "Hmisc" and using Google, I can't find the answer. > > > > If I use stat_summary(fun.data="mean_cl_boot") in ggplot to generate > > 95% > > confidence intervals, how many bootstrap iterations are preformed by > > default? Can this be changed? I would at least like to be able

Ben Bolker

Wed, Nov 9, 2011 1:30 PM

David Winsemius <dwinsemius <at> comcast.net> writes:

In defense of the OP, this is a very confusing situation.
 mean_cl_boot is a ggplot2 function that wraps smean.cl.boot
from the Hmisc package: it's almost impossible to figure this
out from looking at the raw code of mean_cl_boot, although the
help page for ?mean_cl_boot does reference smean.cl.boot.
  ?smean.cl.boot (in Hmisc, so you'll need to have that package
loaded) has a B=1000 parameter for bootstrapping.
   I don't know if stat_summary(fun.data="mean_cl_boot",B=10000)
will work or not, but it would be worth a try (try setting B
to a small number and see if your CIs get very noisy, or set
it to a large number and see if your plot starts taking a lot
longer to compute ...)

ggplot stat_summary(mean_cl_boot)

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