Title: Asymptotic properties of ML and REML for nested error regression models
Authors: Ziyang Lyu - University of New South Wales (Australia) [presenting]
Abstract: Asymptotic results are considered for the maximum likelihood and restricted maximum likelihood (REML) estimators of the parameters in the nested error regression model when both of the number of independent clusters and the cluster sizes (the number of observations in each cluster) go to infinity. A set of conditions is given under which the estimators are shown to be asymptotically normal. There are no restrictions on the rate at which the cluster size tends to infinity.