Le ven. 13 juin à 13:55, Ben Bolker a écrit :
Bluder Olivia <olivia.bluder <at> k-ai.at> writes:
Hello,
I'm trying to calculate the Maximum likelihood estimators for a
dataset
which contains censored data.
I started by using the function "nlm", but isn't there a separate
method
for doing this for e.g. the "weibull" and the "log-normal"
distribution?
Thanks,
Olivia
This is not *quite* enough detail about what you
want to do. Can you (as the posting guide suggests!)
give us a small example of what you want to do? You may be able
to do this via the survreg() command in the survival
package, or you may want to do it yourself by constructing
a log-likelihood function with dweibull() for uncensored
data and pweibull() for censored data [or dlnorm/plnorm].
If you want to go the second route, function coverage() in package
actuar will build the censored density function for you. You can then
feed this function to fitdistr() just like for "usual" ML estimation.
HTH Vincent
Ben Bolker
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
