Hi I am trying to carry out some maximum likelihood estimation and I'm not making much headway, and I'm hoping that someone will be able to point me in the right direction.
I am modelling mortality statistics. One way to do this is to model the mortality rate (or, more accurately, log of the mortality rate, log_m) as (say) a constant plus a proportion of age, plus time, so: r_1 <- lm(formula=log_m ~ age + time) summary(r_1) However, an alternative approach is to use try and estimate the number of deaths from the poisson mean mortality rate, and the number of people, with the poisson mean being defined in terms of age and time (And a constant). Conceptually I can see how this should work, in terms of linking the poisson probabilities together at each age and optimising the coefficients on age and time to maximise the log likelihood, but I cannot work out how to express this in R. Hopefully this outlines what I'm trying to do - any ideas gratefully received. ______________________________________________ [email protected] 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.
