spaMM (2.4.35)

Mixed-Effect Models, Particularly Spatial Models.

https://www.r-project.org
http://kimura.univ-montp2.fr/~rousset/spaMM.htm
http://cran.r-project.org/web/packages/spaMM

Inference in mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta). 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, pbapply, proxy, Rcpp, lme4, maps, multilevel, rcdd, lpSolveAPI, pedigreemm, foreach, testthat, minqa, rsae, blackbox, Infusion, IsoriX

Released 9 months ago.