Inference based on models with or without spatially-correlated random effects, multivariate responses, or non-Gaussian random effects (e.g., Beta). Variation in residual variance (heteroscedasticity) can itself be represented by a mixed-effect model. Both classical geostatistical models (Rousset and Ferdy 2014 <doi:10.1111/ecog.00566>), and Markov random field models on irregular grids (as considered in the 'INLA' package, <https://www.r-inla.org>), can be fitted, with distinct computational procedures exploiting the sparse matrix representations for the latter case and other autoregressive models. Laplace approximations are used for likelihood or restricted likelihood. Penalized quasi-likelihood and other variants discussed in the h-likelihood literature (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) are also implemented.
Version: 4.6.1 Depends: R (≥ 3.5.0) Imports: methods, stats, graphics, Matrix, MASS, proxy, Rcpp (≥ 0.12.10), nlme, nloptr, minqa, pbapply, cli, gmp (≥ 0.6.0), ROI, boot, geometry (≥ 0.4.0), numDeriv, backports, reformulas LinkingTo: Rcpp, RcppEigen (≥ 0.3.3.5.0) Suggests: maps, testthat, rcdd, foreach, future, future.apply, RANN, Infusion (≥ 1.3.0), IsoriX (≥ 0.8.1), blackbox (≥ 1.1.25), RSpectra, ROI.plugin.glpk, lme4, rsae, multilevel, agridat, fmesher Enhances: multcomp, RLRsim, lmerTest, emmeans Published: 2025-06-27 DOI: 10.32614/CRAN.package.spaMM Author: François Rousset [aut, cre, cph], Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut] Maintainer: François Rousset <francois.rousset at umontpellier.fr> License: CeCILL-2 URL: https://gitlab.mbb.univ-montp2.fr/francois/spamm-ref NeedsCompilation: yes SystemRequirements: GNU Scientific Library (GSL) Citation: spaMM citation info Materials: NEWS In views: MixedModels, Spatial CRAN checks: spaMM results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=spaMM to link to this page.
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