Hello, I am searching for a way to generate random values from a multivariate
mixture distribution. For starters, one could create a mixture distribution
consisting of a gamma or normal distribution and then a tail/spike of values in
a normal distribution (eg as in Figure 1, A Eyre-Walker, PD Keightley. 2007.
The distribution of fitness effects of new mutations. Nature Review Genetics 8:
610-618)
I am not certain how to implement this in the R environment. The implementation
becomes even more difficult if one wants to generalize this distribution to
multiple variables that are related to one another via some correlation
structure. The analogous situation is a multivariate normal distribution with
the shape given by the covariance matrix.
What I need for my research program is to generate values for each of 3 random
variables with ("one-dimensional") distributions as in Figure 1 and yet
simultaneously choose a value for each variable so that the resolved values are
correlated in some way (eg if a high value for variable 1 is chosen, it is
likely that values 2 and 3 are low).
Thanks in advance for the help.
Patrick SoprovichBiology Department, Dalhousie University
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
