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: 1.3.0
Depends: R (≥ 3.0.0)
Imports: stats, graphics, Matrix, MASS, lpSolveAPI (≥, proxy, geometry, Rcpp (≥ 0.11.0), nlme
LinkingTo: Rcpp, RcppEigen
Suggests: maps
Published: 2014-09-10
Author: François Rousset [aut, cre, cph], Jean-Baptiste Ferdy [aut, cph]
Maintainer: François Rousset <francois.rousset at>
License: CeCILL-2
NeedsCompilation: yes
Citation: spaMM citation info
In views: Spatial
CRAN checks: spaMM results


Reference manual: spaMM.pdf
Package source: spaMM_1.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: spaMM_1.3.0.tgz, r-oldrel: spaMM_1.3.0.tgz
OS X Mavericks binaries: r-release: spaMM_1.3.0.tgz
Old sources: spaMM archive