spaMM: Mixed Models, Particularly Spatial GLMMs

Implements a collection of functions for inference in mixed models. It was developed in particular for GLMMs with spatial correlations, but also fits models with non-Gaussian random effects (e.g., Beta Binomial, or negative-binomial mixed models). Heteroskedasticity can further be fitted by a linear model. The algorithms are currently various Laplace approximations methods for ML or REML, in particular h-likelihood and penalized-likelihood methods.

Version: 1.4.1
Depends: R (≥ 3.0.0)
Imports: stats, graphics, Matrix, MASS, lpSolveAPI (≥ 5.5.0.14), proxy, geometry, Rcpp (≥ 0.11.0), nlme
LinkingTo: Rcpp, RcppEigen
Suggests: maps, testthat, lme4
Published: 2014-11-09
Author: François Rousset [aut, cre, cph], Jean-Baptiste Ferdy [aut, cph]
Maintainer: François Rousset <francois.rousset at univ-montp2.fr>
License: CeCILL-2
URL: http://www.r-project.org, http://kimura.univ-montp2.fr/~rousset/spaMM.htm
NeedsCompilation: yes
Citation: NA
Materials: NA
In views: Spatial
CRAN checks: spaMM results

Downloads:

Reference manual: spaMM.pdf
Package source: spaMM_1.4.1.tar.gz
Windows binaries: r-devel: spaMM_1.4.1.zip, r-release: spaMM_1.4.1.zip, r-oldrel: spaMM_1.4.1.zip
OS X Snow Leopard binaries: r-release: spaMM_1.4.1.tgz, r-oldrel: spaMM_1.4.1.tgz
OS X Mavericks binaries: r-release: spaMM_1.4.1.tgz
Old sources: spaMM archive