Composite likelihood approach is implemented to estimating statistical models for spatial ordinal and proportional data based on Feng et al. (2014) <doi:10.1002/env.2306>. 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.
| Version: | 1.1.2 |
| Depends: | R (≥ 3.2.0) |
| Imports: | AER (≥ 1.2-5), pbivnorm (≥ 0.6.0), MASS (≥ 7.3-45), magic (≥ 1.5-6), survival (≥ 2.37-5), clordr (≥ 1.0.2), doParallel (≥ 1.0.11), foreach (≥ 1.2.0), utils, stats |
| Published: | 2018-02-23 |
| Author: | Ting Fung (Ralph) Ma [cre, aut], Wenbo Wu [aut], Jun Zhu [aut], Xiaoping Feng [aut], Daniel Walsh [ctb], Robin Russell [ctb] |
| Maintainer: | Ting Fung (Ralph) Ma <tingfung.ma at wisc.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | clespr results |
| Reference manual: | clespr.pdf |
| Package source: | clespr_1.1.2.tar.gz |
| Windows binaries: | r-devel: clespr_1.1.2.zip, r-release: clespr_1.1.2.zip, r-oldrel: clespr_1.1.2.zip |
| macOS binaries: | r-release: clespr_1.1.2.tgz, r-oldrel: clespr_1.1.2.tgz |
| Old sources: | clespr archive |
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