Efficiency of quasi-likelihood estimation for spatially correlated binary data on LpLp spaces

For spatially correlated binary data with correlation across the study region in RdRd space, d⩾2d⩾2, there is no literature that discusses estimation problems concerning various LpLp norms. In this paper, the concept of quasi-likelihood (QL) estimating equations is utilized to address this problem. We first generalize the asymptotic properties of QL estimates to high dimensional spaces for certain mixing conditions. A series of simulations is then conducted to evaluate the performance of QL estimating equations on various LpLp norms and working correlation matrices. Some interesting results for the relationship between the efficiencies of QL estimates and regression coefficients can also be found through the simulation.