Composite Likelihood Estimation for Spatial Data
Description
Composite likelihood approach is implemented to estimating statistical models for spatial ordinal and proportional data based on Feng et al. (2014) . Parameter estimates are identified by maximizing composite log-likelihood functions using the limited memory BFGS optimization algorithm with bounding constraints, while standard errors are obtained by estimating the Godambe information matrix.