Hi all,
I just wanted to add that I am looking for a solution that's in R ... to
handle this...
And also, in a given sample, the correct data are of the majority and the
noise are of the minority.
Thank you!
On Tue, Jan 24, 2012 at 4:09 PM, Michael <comtech....@gmail.com> wrote:
> Hi all,
>
> I have data which are unfortuantely comtaminated by noise.
>
> We knew that the noise is at different level than the correct data, i.e.
> the noise data can be easily picked out by human eyes.
>
> It looks as if there are two people that generated the two very different
> data with different mean levels, and they got mixed together.
>
> i.e. assming the two data are following unknown distribution DF,
>
> and the two mean levels are u1 and u2... (unknown)
>
> Then the correct data are generated by DF(u1)
>
> and the noise are generated by DF(u2),
>
> and they got mixed...
>
> Now, how do I flag those suspicious data? At least is there a way I could
> answer the question:
>
> Given a sample of mixed data - are these data generated from the
> above-mentioned two sources, or the data are indeed generated from one
> source only.
>
> i.e. are there two substantially distinct species in the given data?
>
> Thanks a lot!
>
>
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