A0797
Title: Hierarchical Bayes nested error regression models with spatial random effects
Authors: Hee Cheol Chung - UNC Charlotte (United States) [presenting]
Abstract: In many applications, the population means of geographically proximate small areas exhibit spatial variation. When auxiliary variables fail to adequately capture this spatial pattern, the residual variation is absorbed into the random effects, violating the assumption of independent and identically distributed random effects. This issue becomes more significant when predicting means for low or non-sampled small areas, as these predictions depend almost entirely on auxiliary variables. To address this, spatial nested error regression models are proposed that account for interdependencies between small areas by incorporating spatially correlated random effects.
