Here is a similar example I'm using for my course, students seemed to enjoy
the simulation part at the end.
HTH,
Peter
*t<-100; alpha<-0.01; F<-0.6; N0<-80*
*r<-c(r0, numeric(t))*
*for (i in 1:t) *
*r[i+1]<- {*
*runif(1,0.2,1.8)*
*}*
*N<-c(N0, numeric(t))*
*for (i in 1:t) {*
*N[i+1]<-*
Jeff,
I am not sure why you need 100 random numbers for r and K, but if your goal
is to get stochastic state-space model, you need to define the error term
as a separate parameter and run the loop 100 times with the *same* fixed
parameter values. When you do this, then you need to be aware of
para
Hi everyone,
I would like to create stochastic population models for an undergraduate
course.
The goal would be to have students run models, record, results, change
parameters, and make inferences on changing the effects.
I understand how to draw from distributions, I hit a knowledge wall with
l
Hi Class,My data are number of species per site (specie richness). Regarding
the sensitivity of the species richness to the spatial scale I believe and I am
pretty sure that I can assume that all species react at the same way to the
spatial scale since I am working only with forest in which ecol
