Package: clespr
Type: Package
Title: Composite Likelihood Estimation for Spatial Data
Version: 1.1.2
Authors@R: c(
    person("Ting Fung (Ralph)", "Ma", email = "tingfung.ma@wisc.edu", role = c("cre", "aut")),
    person("Wenbo", "Wu", email = "wenbowu@umich.edu", role = "aut"),
    person("Jun", "Zhu", email = "jzhu@stat.wisc.edu", role = "aut"),
    person("Xiaoping", "Feng", role = "aut"),
    person("Daniel", "Walsh", role= "ctb"),
    person("Robin", "Russell", role= "ctb"))
Maintainer: Ting Fung (Ralph) Ma <tingfung.ma@wisc.edu>
Description: 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.
License: GPL-2
LazyData: TRUE
RoxygenNote: 6.0.1
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
NeedsCompilation: no
Packaged: 2018-02-23 04:23:42 UTC; Ralph
Author: Ting Fung (Ralph) Ma [cre, aut],
  Wenbo Wu [aut],
  Jun Zhu [aut],
  Xiaoping Feng [aut],
  Daniel Walsh [ctb],
  Robin Russell [ctb]
Repository: CRAN
Date/Publication: 2018-02-23 19:05:06 UTC
Built: R 4.2.0; ; 2023-07-11 02:23:28 UTC; unix
