[R] Using error in histograms

[Greg Snow]

The logspline package does density estimation in a different way than KDE, but it does allow for interval censored data (I know this value is between a and b, but not where in that range) using the oldlogspline function.  This may be what you are looking for.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111


> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Kristof Ostir
> Sent: Thursday, May 05, 2011 4:16 AM
> To: r-help at r-project.org
> Subject: [R] Using error in histograms
> 
> Hello!
> 
> I am trying to produce a histogram of measurement data (orientation of
> archaeological structures) that are a subject to measurement error.
> The normal histogram just computes frequencies, but does not take into
> account that a particular value is spread over a range of values (in
> my case the spread is different for reach measurement and is larger
> than the bin size).
> 
> The closest approach is kernel density estimation (in the image is a
> comparison of histogram and KDE):
> http://en.wikipedia.org/wiki/Kernel_density_estimation
> http://en.wikipedia.org/wiki/File:Comparison_of_1D_histogram_and_KDE.pn
> g
> However in my case the kernel size is different for each value. I
> wrote a program in IDL that performs the plotting, but am just
> wondering if such a function is available in R. Basically it is a
> problem of summing (and later plotting) several data distributions.
> 
> I would appreciate also any hint to a book that might be dealing with
> the problem. I am not an expert in statistics and I might not be using
> use the correct terminology in web searches.
> 
> Regards,
> 
> Kristof
> 
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