Inference in mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta-Binomial). Variation in residual variance (heteroscedasticity) can itself be represented by a generalized linear mixed model. Various approximations of likelihood or restricted likelihood are implemented, in particular h-likelihood (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) and Laplace approximation.
Version: |
2.3.0 |
Depends: |
R (≥ 3.2.0) |
Imports: |
methods, stats, graphics, Matrix, MASS, proxy, Rcpp (≥
0.12.10), nlme, nloptr |
LinkingTo: |
Rcpp, RcppEigen |
Suggests: |
maps, testthat, lme4, rsae, rcdd, e1071, foreach, pedigreemm, minqa |
Published: |
2018-01-18 |
Author: |
François Rousset [aut, cre, cph],
Jean-Baptiste Ferdy [aut, cph],
Alexandre Courtiol [aut],
GSL authors [ctb] (src/gsl_bessel.*) |
Maintainer: |
François Rousset <francois.rousset at umontpellier.fr> |
License: |
CeCILL-2 |
URL: |
https://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 |