Suggested package to add (glmmrBase, glmmrOptim)

[samuel-watson]

Hi, I wanted to suggest adding a resource to the CRAN task view on mixed models. I've been developing a GLMM model fitting package for R (currently on CRAN as glmmrBase v0.4.6 ), which I wanted to suggest is added to the mixed model task view page. Just as an overview of what it does, I've put a summary below. There's a linked paper under review at JSS, which is online here. The github page is here and an (unfinished) page of tutorials and the like here.

Summary of package functionality:

• Frequentist model fitting using Markov chain monte carlo Maximum likelihood and also Laplace approximation. The MCMC part of the maximum likelihood algorithms uses either Stan or the in-built HMC sampler (Stan much better though!)
• Currently a range of models and link functions. Random effects structures include exchangeable, autoregressive/exponential, matern (and associated functions), some compactly supported functions for inducing sparsity. The next version will also include nearest neighbour Gaussian process approximation covariance. Families are Gaussian, Binomial, Poisson, Beta, and Gamma. It also supports non-linear fixed effect specifications using a first-order approximation with autodifferentiation. I'm planning to add further models in future versions including splines.
• The R package includes a large number of functions providing access to various calculations and matrices to support other applications (e.g. information matrices, gradient and likelihood calculations). It's built on R6 object orientated classes on R side. It also provides power calculations and similar.
• It provides some different standard errors including GLS, robust sandwich estimator, and the Kenward-Roger correction.
• There is currently another dependent package on CRAN (glmmrOptim ) that has several (c-)optimal design algorithms based on GLMMs. The main library is header only in glmmrBase to help importing into other projects (for example, it is used in this online randomised trial designer). I'll push an update to another package soon that estimates log Gaussian cox processes using the GLMM functionality and the Gaussian process approximations above.

I thought the package may be useful to some people, so hoping to add it to the CRAN page. Please let me know if you would like any further information.

[bbolker]

I've added glmmrBase, but not (yet) glmmrOptim