Composite likelihood parameter estimate and asymptotic covariance matrix are calculated for the spatial ordinal data with replications, where spatial ordinal response with covariate and both spatial exponential covariance within subject and independent and identically distributed measurement error. Parameter estimation can be performed by either solving the gradient function or maximizing composite loglikelihood. Parametric bootstrapping is used to estimate the Godambe information matrix and hence the asymptotic standard error and covariance matrix with parallel processing option. Moreover, the proposed surrogate residual, which extends the results of Liu and Zhang (2017) <doi: 10.1080/01621459.2017.1292915>, can act as a useful tool for model diagnostics.
Package details 


Author  Ting Fung (Ralph) Ma [cre, aut], Pingping Wang [aut], Jun Zhu [aut], Dipankar Bandyopadhyay [ctb], Yincai Tang [ctb] 
Maintainer  Ting Fung (Ralph) Ma <[email protected]> 
License  GPL2 
Version  1.5.0 
Package repository  View on CRAN 
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