clordr: Composite Likelihood Inference for Spatial Ordinal Data with Replications

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 log-likelihood. Parametric bootstrapping is used to estimate the Godambe information matrix and hence the asymptotic standard error and covariance matrix with parallel processing option.

Version: 1.3.0
Imports: pbivnorm (≥ 0.6.0), MASS (≥ 7.3-45), rootSolve (≥ 1.7), doParallel (≥ 1.0.11), foreach (≥ 1.2.0), utils, stats, ttutils
Published: 2018-04-19
Author: Ting Fung (Ralph) Ma [cre, aut], Pingping Wang [aut], Jun Zhu [aut], Dipankar Bandyopadhyay [ctb], Yincai Tang [ctb]
Maintainer: Ting Fung (Ralph) Ma <tingfung.ma at wisc.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: clordr results

Downloads:

Reference manual: clordr.pdf
Package source: clordr_1.3.0.tar.gz
Windows binaries: r-devel: clordr_1.3.0.zip, r-release: clordr_1.3.0.zip, r-oldrel: clordr_1.3.0.zip
OS X binaries: r-release: clordr_1.3.0.tgz, r-oldrel: clordr_1.3.0.tgz
Old sources: clordr archive

Reverse dependencies:

Reverse imports: clespr

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