See in-line below.
cheers,
Rolf Turner
On 04/01/14 12:48, Stefan Mühlbauer wrote:
Hello!
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I am having two variables x and y (whereas y is a set of raster images) and
want to
quantify the correlation between x and y by calculating the Pearson
Correlation Coefficient. In order to ensure how signficant the correlation
results are, I am interested in getting the p-value (<0.1) for this two
tailed student-t distribution. The problem now is: I have a very small
number of observations and therefore would need to make a permutation test,
which enables to simulate a high number of observations.
You are deluding yourself.
Â
So far I did the Pearsons Correlation and Significance test, but without
applying permutaton test. I used following formula for obtaining the
p-values:
Â
T = r*(sqrt(n-2))/sqrt(1-r²)
p-value = 2 P [ T(n-2) ≥ |t|]
r...Pearson correlation coefficient
n...degree of freedom
Â
Now I have to redo everything using a permutation test. I thought of
implementing 'lmp' function in 'calc' function of raster package.
The two variables I wanted to save within two lists. I am interested in getting
the p-value for each pixel. Can this work?
Â
I will very much appreaciate your help!
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