Ok, I got it.
smean.cl.boot(x, conf.int=.95, B=1000, na.rm=TRUE, reps=FALSE)
Looks like its 1000.
Cool.
Thanks for the help,
Nate
On Wed, Nov 9, 2011 at 1:35 PM, Nathan Miller <natemille...@gmail.com>wrote:
> Sorry, I didn't realize I was being so obscure.
>
> Within ggplot it is possible to use stat_summary() to generate confidence
> intervals about a mean. One method for generating these CI assumes
> normality. The other uses bootstrapping to generate the CI. I am using the
> second method which requires code like this
>
> stat_summary(fun.data="mean_cl_boot", geom="errorbar",width=0.1,colour =
> "red")
>
> I've added some extra flourishes to make them look like errorbars, alter
> the width and specify color.
>
> I would like some details regarding how this bootstrapped CI is
> calculated. If I type "?mean_cl_boot" at the R command line I get a minimal
> help file for "wrap_hmisc {ggplot2}" which is described "wrap up a
> selection of Hmisc to make it easy to use with stat_summary"
>
> I did not mean to suggest that ggplot2 calls Hmisc when I run
> stat_summary(), but simply that it appears that stat_summary() seems to
> have been based upon a selection of Hmisc, hence I went looking in Hmisc to
> try to find details regarding stat_summary(). I was unsuccessful in this
> attempt.
>
> I don't believe a great deal of debugging is necessary. I am simply
> looking for details regarding how "mean_cl_boot" works. If you don't have
> information regarding how it works (such as the default number of
> resamplings) there is no need to respond.
>
> Thanks for any assistance,
> Nate
>
>
>
>
> On Wed, Nov 9, 2011 at 1:10 PM, David Winsemius <dwinsem...@comcast.net>wrote:
>
>>
>> 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 to report
>>> the number of boot strap interations used to generate the CIs.
>>>
>>> I haven't been able to find "mean_cl_boot" as a function itself or
>>> something ressembling it in the Hmisc documentation, but it seems as
>>> though
>>> Hmisc is wrapped up in stat_summary() and is called to compute
>>> "mean_cl_boot".
>>>
>>
>> You seem really, really confused (and you offer very little in the way of
>> context to support debugging efforts). You are referring to ggplot
>> functions. As far as I know there is no connection between the Hmisc and
>> ggplot (or ggplot2) packages. Al things change, I know, but Frank just
>> completed switching over to Lattice a couple of years ago.
>>
>>
>> --
>> David Winsemius, MD
>> West Hartford, CT
>>
>>
>
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
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.
