spaMM: Mixed Models, Particularly Spatial GLMMs

Inference in mixed models, including GLMMs with spatial correlations and models with non-Gaussian random effects (e.g., Beta Binomial, or negative-binomial mixed models). Heteroscedasticity 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: 1.9.16
Depends: R (≥ 3.1.0)
Imports: methods, stats, graphics, Matrix, MASS, lpSolveAPI (≥ 5.5.0.14), proxy, geometry (≥ 0.3.6), Rcpp (≥ 0.11.0), nlme, mvtnorm, nloptr
LinkingTo: Rcpp, RcppEigen
Suggests: maps, testthat, lme4, rsae, ff, rasterVis, rgdal, rcdd
Published: 2016-07-22
Author: François Rousset [aut, cre, cph], Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [ctb], Dirk Eddelbuettel [ctb] (ziggurat rnorm sources), GSL authors [ctb] (src/gsl_bessel.*)
Maintainer: François Rousset <francois.rousset at umontpellier.fr>
BugReports: NA
License: CeCILL-2
URL: http://www.r-project.org, http://kimura.univ-montp2.fr/~rousset/spaMM.htm
NeedsCompilation: yes
Citation: spaMM citation info
Materials: NEWS
In views: Spatial
CRAN checks: spaMM results

Downloads:

Reference manual: spaMM.pdf
Package source: spaMM_1.9.16.tar.gz
Windows binaries: r-devel: spaMM_1.9.16.zip, r-release: spaMM_1.9.16.zip, r-oldrel: spaMM_1.9.16.zip
OS X Mavericks binaries: r-release: spaMM_1.9.16.tgz, r-oldrel: spaMM_1.9.16.tgz
Old sources: spaMM archive

Reverse dependencies:

Reverse imports: blackbox, Infusion