If you're interested in comparing empirical to simulation
distributions, I see two alternatives to your density() approach
(which will be sensitive to your choice of bandwidth). Both of the
following have been used in my field to look at the fit of empirical
response time data to models of human in
If you make your calls to density with common lenth and interval
parameters you should be able to get better "registration":
?density
# this example sums the squared differences
x <- rnorm(200,1,1)
x2 <- rnorm(200,1,1)
d1 <- density(x, n=512, from=-1, to= 4)
d2 <- density(x2, n=512, from=-
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
re
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