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). 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: |
1.6.2 |
| Depends: |
R (≥ 3.0.0) |
| Imports: |
methods, stats, graphics, Matrix, MASS, lpSolveAPI (≥
5.5.0.14), proxy, geometry, Rcpp (≥ 0.11.0), nlme, mvtnorm |
| LinkingTo: |
Rcpp, RcppEigen |
| Suggests: |
maps, testthat, lme4, rsae, ff, rasterVis, rgdal |
| Published: |
2015-11-01 |
| Author: |
François Rousset [aut, cre, cph],
Jean-Baptiste Ferdy [aut, cph],
GSL authors [ctb] (src/gsl_bessel.*) |
| 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: |
spaMM citation info |
| Materials: |
NEWS |
| In views: |
Spatial |
| CRAN checks: |
spaMM results |