dear R experts: I am trying to plot an empirical likelihood function in 3d.
The values are not over a regular grid---I just searched the likelihood
function to find the optimal value, and then computed a few values around
it. (each point in the likelihood function takes a very long time to
compute.)
the likelihood values now sit in a csv file that has three
columns, "mu", "sd", and "v". I would like to look at my 3d plots to find
out how well or badly behaved my likelihood function is (and then compute a
Hessian, my next task).
Is persp() the correct function for this task? something else?
is there a wrapper that takes my x, y, and z values (which come in almost
random order), and puts them into the format that persp() needs?
pointers appreciated.
sincerely,
/iaw
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
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.
