Skip to content
Snippets Groups Projects
Commit a8b08b0d authored by francois's avatar francois
Browse files

Update README.md

parent e0aa5cb2
Branches
No related tags found
No related merge requests found
......@@ -37,7 +37,7 @@ Also available here is the [Supplementary Appendix G](http://kimura.univ-montp2.
For some substantial use of various features of `spaMM`, see e.g. the [IsoriX project](https://github.com/courtiol/IsoriX), or a story about [social dominance in hyaenas](https://doi.org/10.1038/s41559-018-0718-9), or [yet another depressing story about climate change](https://doi.org/10.1038/s41467-019-10924-4), or [the life-history of mothers of twins](https://doi.org/10.1038/s41467-022-30366-9), or a comparison of prediction by LMMs and by random-forest methods (in supplementary material of [a paper on protected area personnel](https://doi.org/10.1038/s41893-022-00970-0)) or [analyses of dyadic interactions in mandrills](https://doi.org/10.7554/eLife.79417).
Initial development drew inspiration from work by Lee and Nelder on _h_-likelihood (e.g. [Lee, Nelder & Pawitan](https://doi.org/10.1201/9781420011340), 2006; [Lee & Lee](http://dx.doi.org/10.1007/s11222-011-9265-9) 2012; see also [Molas and Lesaffre](http://dx.doi.org/10.1002/sim.3852), 2010), and `spaMM` retains from that work several distinctive features, such as specific methods to fit models with non-gaussian random effects, structured dispersion models with random effects, and implementation of several variants of Laplace and PQL approximations. However, later versions have increasingly relied on additional insights. Notably, the default likelihood approximation now goes beyond those discussed in these works, and is the same Laplace approximation ([Skaug & Fournier, 2006](https://doi.org/10.1016/j.csda.2006.03.005)) as in [TMB](https://cran.r-project.org/web/packages/TMB) and packages based on TMB, in particular where this departs from what is discussed in the _h_-likelihood literature (i.e., for GLM families with non-canonical link, or response families not of the GLM class).
Initial development drew inspiration from work by Lee and Nelder on _h_-likelihood (e.g. [Lee, Nelder & Pawitan](https://doi.org/10.1201/9781420011340), 2006; [Lee & Lee](http://dx.doi.org/10.1007/s11222-011-9265-9) 2012; see also [Molas and Lesaffre](http://dx.doi.org/10.1002/sim.3852), 2010), and `spaMM` retains from that work several distinctive features, such as specific methods to fit models with non-gaussian random effects, structured dispersion models with random effects, and implementation of several variants of Laplace and PQL approximations. However, later versions have increasingly relied on additional insights. Notably, the default likelihood approximation now goes beyond those discussed in these works, and is the same Laplace approximation as in `TMB` ([Kristensen et al., 2016](https://doi.org/10.18637/jss.v070.i05)) and packages based on `TMB`, in particular where this departs from what is discussed in the _h_-likelihood literature (i.e., for GLM families with non-canonical link, or response families not of the GLM class).
## Credits
Initial development was supported by a PEPS grant from the CNRS and University of Montpellier.
0% Loading or .
You are about to add 0 people to the discussion. Proceed with caution.
Please register or to comment