A1350
Title: Robust estimation of a dynamic spatiotemporal model with structural change for count data
Authors: Charlene Mae Celoso - University of the Philippines Diliman (Philippines) [presenting]
Abstract: A dynamic spatiotemporal model with count response is estimated with a hybrid of forward search algorithm and bootstrap embedded into the backfitting algorithm. The method is evaluated for its robustness in some count data generating process. Simulation studies indicated that the method performs better in terms of median absolute deviation (MAD) when there are more time points than observations units in space and when the covariates contributes more than the spatial externalities. Also, the bias and the standard error of the parameter estimates indicated its suitability for count data across a wide variety of conditions.
