Hello! I'm a college undergrad desperately trying to finish up my thesis. I have a dataset on the distribution of a grassland bird from the Breeding Bird Survey. I have a very straightforward and simple version of the logistic growth model to describe changes in this bird's abundance over time. The variables are the natural birth rate, mortality, and carrying capacity. The equation itself looks like this: birds <- c*birds + b*birds*(1-birds/K) where c = mortality, b = birth rate, and K = carrying capacity.
I'm trying to find the optimal value of K and I've been using the optim function. The problem is that it doesn't really work. My code is below: b<-1.22 c<-0.55 bird<-bird.density[0] eqn1<- function(K1, bird) { for (i in 1:8) { b<-1.22 c<-0.55 bird <- 0.55*bird + b*bird*1-b*bird*bird/K } } k1<-optim(c(0,10),eqn) I realize this is a painfully amateurish question, but I really appreciate any help! The other tricky part about this is that it looks like there are 3 distinct time periods where the bird is increasing, declining, and increasing again. I'm thinking that there are 3 different carrying capacity values, but my understanding of optim is that it can only optimize one parameter variable at a time. So I was going to take the brute force approach of artificially breaking up the equation into 3 parts (i.e. make eqn1, eqn2, and eqn3, and optimize each separately, with the input values for the later two functions coming from the last number of birds from the previous loop). Thank you all very much! charlotte ______________________________________________ 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.