Estimating Functions in Chaotic Systems
Subhash R. Lele · Journal of the American Statistical Association · 1994
Berliner considered Bayesian and likelihood-based approaches for estimation and prediction in a chaotic system with measurement error. This article proposes the use of estimating functions for this problem. Logistic and exponential maps are analyzed. Estimators are shown to be consistent and asymptotically normal. Small-sample behavior is studied with simulations.