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). Various approximations of likelihood or restricted likelihood are implemented, in particular Laplace approximation and h-likelihood (Lee and Nelder 2001 ). Both classical geostatistical models, and Markov random field models on irregular grids (as considered in the 'INLA' package, < http://www.r-inla.org>), can be fitted. Variation in residual variance (heteroscedasticity) can itself be represented by a mixed-effect model.


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install.packages("spaMM")

3.5.0 by Fran├žois Rousset, 19 days ago


https://www.r-project.org, https://kimura.univ-montp2.fr/~rousset/spaMM.htm


Browse source code at https://github.com/cran/spaMM


Authors: Fran├žois Rousset [aut, cre, cph] , Jean-Baptiste Ferdy [aut, cph] , Alexandre Courtiol [aut] , GSL authors [ctb] (src/gsl_bessel.*)


Documentation:   PDF Manual  


Task views: Analysis of Spatial Data


CeCILL-2 license


Imports methods, stats, graphics, Matrix, MASS, proxy, Rcpp, nlme, nloptr, minqa, pbapply, crayon, gmp, ROI, boot

Suggests maps, testthat, lme4, rsae, rcdd, pedigreemm, foreach, multilevel, Infusion, IsoriX, blackbox, RSpectra, ROI.plugin.glpk

Enhances multcomp

Linking to Rcpp, RcppEigen


Imported by Infusion, IsoriX, blackbox.

Suggested by DHARMa.


See at CRAN