spaMM: Mixed models, particularly spatial GLMMs

Implements a collection of functions for inference in hierarchical generalized linear models (HGLMs), which include GLMMs but also non-Gaussian random effects (e.g. Beta Binomial). It was developed in particular for GLMMs with spatial correlations. 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: 1.1
Imports: Matrix, MASS, lpSolveAPI (≥ 5.5.0.14)
Suggests: nlme
Published: 2014-01-17
Author: Fran├žois Rousset [aut, cre, cph], Jean-Baptiste Ferdy [aut, cph]
Maintainer: Fran├žois 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: spaMM citation info
CRAN checks: spaMM results

Downloads:

Reference manual: spaMM.pdf
Package source: spaMM_1.1.tar.gz
OS X binary: spaMM_1.1.tgz
Windows binary: spaMM_1.1.zip
Old sources: spaMM archive