Composite Likelihood Estimation for Spatial Data

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.


Reference manual

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1.1.2 by Ting Fung (Ralph) Ma, 4 years ago

Browse source code at

Authors: Ting Fung (Ralph) Ma [cre, aut] , Wenbo Wu [aut] , Jun Zhu [aut] , Xiaoping Feng [aut] , Daniel Walsh [ctb] , Robin Russell [ctb]

Documentation:   PDF Manual  

GPL-2 license

Imports AER, pbivnorm, MASS, magic, survival, clordr, doParallel, foreach, utils, stats

See at CRAN