spaMM (3.2.0)

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Mixed-Effect Models, Particularly Spatial Models.

Inference based on mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta). Both classical geostatistical models, and Markov random field models on irregular grids, can be fitted. 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: crayon, gmp, MASS, Matrix, minqa, nlme, nloptr, pbapply, proxy, Rcpp, ROI, ROI.plugin.glpk, lme4, maps, multilevel, rcdd, pedigreemm, foreach, testthat, rsae, RSpectra, blackbox, Infusion, IsoriX
Enhances: multcomp
Reverse suggests: DHARMa

Released about 1 month ago.

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