spaMM (2.1.6)

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, or negative-binomial mixed models). Variation in residual variance is handled and can be modelled as a linear model. The algorithms are currently various Laplace approximations methods for likelihood or restricted likelihood, in particular h-likelihood and penalized-likelihood methods.

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, ff, lme4, maps, rcdd, foreach, testthat, rsae

Released over 2 years ago.