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.

Documentation

Manual: spaMM.pdf
Vignette: None available.

Maintainer: François Rousset <francois.rousset at umontpellier.fr>

Author(s): François Rousset*, Jean-Baptiste Ferdy*, Alexandre Courtiol*, Dirk Eddelbuettel* (ziggurat rnorm sources), GSL authors* (src/gsl_bessel.*)

Install package and any missing dependencies by running this line in your R console:

install.packages("spaMM")

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
Suggests maps, testthat, lme4, rsae, ff, rasterVis, rgdal, rcdd
Enhances
Linking to Rcpp, RcppEigen
Reverse
depends
Reverse
imports
blackbox, Infusion, IsoriX
Reverse
suggests
Reverse
enhances
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linking to

Package spaMM
Materials
URL http://www.r-project.org http://kimura.univ-montp2.fr/~rousset/spaMM.htm
Task Views Spatial
Version 1.10.0
Published 2016-09-05
License CeCILL-2
BugReports
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks spaMM check results
Package source spaMM_1.10.0.tar.gz