Abstract
Observation error can lead to substantial bias in estimating the parameters of a population model. While maximum-likelihood estimation is possible in principle, it can be extremely difficult in practice due to the complicated behavior of the likelihood function. This note describes a simple method that can be used to fit a population model in the presence of observation error. The method is illustrated using the discrete-time logistic model.
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Published version (
Free)
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
