Hi,
This is my first time posting to the mailing list, so if I'm doing something
wrong, just let me know. I've taken ~1000 samples from 8 biological
replicates, and I want to somehow combine the density functions of the
replicates. Currently, I can plot the density function for each biological
replicate, and I'd like to see how pool of replicates compares to a
simulation I conducted earlier. I can compare each replicate to the
simulation, but there's a fair amount of variability between replicates.
I'd like to take the geometric mean of the density functions at each point
along the x-axis, but when I compute:
> a<-density(A[,1][A[,1]>=0], n=2^15)
> b<-density(A[,3][A[,3]>=0], n=2^15)
> a$x[1]
[1] -70.47504
> b$x[1]
[1] -69.28902
So I can't simply compute the mean across y-values, because the x-values
don't match. Is there a way to set the x-values to be the same for multiple
density plots? Also, there are no negative values in the dataset, so I'd
like to bound the x-axis at 0 if at all possible? Is there a standard way
to combine density functions? Thanks for the advice.
-Aaron Spivak
ps. I thought about just pooling all measurements, but I don't think that's
appropriate because they are from different replicates and the smoothing
kernel depends on the variance in the sample to calculate the distribution.
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