A1263
Title: Inference for spatial autoregressive models using stochastic gradient descent
Authors: Ji Meng Loh - New Jersey Institute of Technology (United States) [presenting]
Gan Luan - New Jersey Institute of Technology (United States)
Abstract: Using stochastic gradient descent (SGD), the procedure is considered to fit spatial auto-regressive models to lattice data, incorporating a recently developed perturbation method to obtain standard errors in addition to model parameter estimates. The SGD update equations are derived, and the results of a simulation study will be presented to examine the empirical coverage of confidence intervals constructed using the perturbation procedure.
