Dear all,
I have the positions of N points spread through some sequence of length L
(L>N), and I would like to know how can do the following:
1- Permute the positions of the N points along the whole sequence.
Assuming a uniform distribution I did: position1 <- runif(N, 1, L)
2- Apply a kernel convolution method to the resulting permuted points profile.
For this I applied the function: d <- density(position1, bw =
"sj")
3- Record the heights of all peaks.
For this I used the estimated density values from the output of the density
function above: heights1 <- d$y
4- Repeat step 1 and 2 to be able to have a distribution of the peaks from the
random data results.
I don´t know how to perform this step!!!
5- Compute the threshold by determining the alfa-level in the empirical CDF of
the null distribution.
Assuming ´heightsALL´ is the output of step 4 I would do this:
plot(ecdf(heightsALL)). But I don´t know how to compute the threshold
6- Apply this threshold to the peaks estimate of the real peaks data, resulting
in a series of significant peaks.
This step can be done by seeing the peaks in the real data that are above the
threshold and classify these as significant at the alfa-level.
The steps mentioned above are better illustrated with a picture that can be
fetched here:
http://www.yousendit.com/transfer.php?action=download&ufid=0E3724F26CA53367
Best regards and thanks in advance,
João Fadista
Ph.d. student
UNIVERSITY OF AARHUS
Faculty of Agricultural Sciences
Dept. of Genetics and Biotechnology
Blichers Allé 20, P.O. BOX 50
DK-8830 Tjele
Phone: +45 8999 1900
Direct: +45 8999 1900
E-mail: Joao.Fadista@agrsci.dk <mailto:Joao.Fadista@agrsci.dk>
Web: www.agrsci.org <http://www.agrsci.org/>
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