spaMM

Description

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.

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  installed size is 39.3Mb
  sub-directories of 1Mb or more:
    R      3.1Mb
    libs  34.9Mb

  installed size is 40.0Mb
  sub-directories of 1Mb or more:
    R      3.1Mb
    libs  35.6Mb

  installed size is  6.1Mb
  sub-directories of 1Mb or more:
    R      2.9Mb
    libs   1.8Mb

Check History

  installed size is 39.3Mb
  sub-directories of 1Mb or more:
    R      3.1Mb
    libs  34.9Mb

  installed size is 40.0Mb
  sub-directories of 1Mb or more:
    R      3.1Mb
    libs  35.6Mb

  installed size is  6.1Mb
  sub-directories of 1Mb or more:
    R      2.9Mb
    libs   1.8Mb

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