[R] smoothing function for proportions
rkoenker at uiuc.edu
Fri Aug 10 17:51:42 CEST 2007
It is not entirely clear what you are using for y values in
but it would appear that it is just the point estimates. I would
using instead -- at each x value -- a few equally spaced quantiles of
the estimated proportions. Implicitly, smooth.spline expects to be
a mean curve to data that has constant variance, so you might also
consider reweighting to approximate this, as well.
url: www.econ.uiuc.edu/~roger Roger Koenker
email rkoenker at uiuc.edu Department of Economics
vox: 217-333-4558 University of Illinois
fax: 217-244-6678 Champaign, IL 61820
On Aug 10, 2007, at 10:23 AM, Rose Hoberman wrote:
> Sorry, forgot to attach the graph.
> On 8/10/07, Rose Hoberman <roseh at cs.cmu.edu> wrote:
>> I am looking for a function that can fit a smooth function to a
>> of estimated proportions, such that the smoothed value is within
>> specified confidence bounds of each proportion. In other words,
>> a small number of trials and large confidence intervals, I would
>> prefer the function to vary smoothly, but given a large number of
>> trials and small confidence intervals, I would prefer the function to
>> lie within the confidence intervals, even if it is not smooth.
>> I have attached a postscript file illustrating a data set I would
>> to smooth. As the figure shows, for large values of x, I have few
>> data points, and so the ML estimate of the proportion varies widely,
>> and the confidence intervals are very large. When I use the
>> smooth.spline function with a large value of spar (the red line), the
>> function is not as smooth as desired for large values of x. When I
>> use a smaller value of spar (the green line), the function fails to
>> stay within the confidence bounds of the proportions. Is there a
>> smoothing function for which I can specify upper and lower limits for
>> the y value for specific values of x?
>> Thanks for any suggestions,
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