spaMM (2.3.0)

Mixed-Effect Models, Particularly Spatial Models.

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 ) and Laplace approximation.

Maintainer: Franois Rousset
Author(s): Franois Rousset [aut, cre, cph], Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut], GSL authors [ctb] (src/gsl_bessel.*)

License: CeCILL-2

Uses: MASS, Matrix, nlme, nloptr, proxy, Rcpp, e1071, lme4, maps, rcdd, pedigreemm, foreach, testthat, minqa, rsae

Released almost 2 years ago.