Hi all, I study epidemiology of soilborne disease. I have this ode model
dS/dt = - (rp(t) X + rs(t) I) * S with X=1 ; rp(t) = ap exp( - bp*t) ; rs(t) = as exp (-0.5 ( ln (t/ds) / bs)² ) The data I have are not directly the infected individuals (which is a hidden state) but the Diseases ones (individuals who show aerial symptoms). I have studied with experiments the relationship between the infected I and the diseases D and I find a delay increasing linearly with a logNormal error. I would like to estimate the parameters of this model but as you can see using an ode solver package and the least square method to fit the model is not a good idea! Do you think it is possible to use a bayesian state space model with I as a Hidden state with this ode epidemiological model ? If not, it is at least possible to fit this ode model using a likelihood method instead of using least square ? Wich R package appears to be the most adapted ? Thank you! Melen ______________________________________________ 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.
