hglm

Implemented here are procedures for fitting hierarchical generalized linear models (HGLM). It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the mean model. As statistical models, HGLMs were initially developed by Lee and Nelder (1996) https://www.jstor.org/stable/2346105?seq=1. We provide an implementation (Ronnegard, Alam and Shen 2010) https://journal.r-project.org/archive/2010-2/RJournal_2010-2_Roennegaard~et~al.pdf following Lee, Nelder and Pawitan (2006) with algorithms extended for spatial modeling (Alam, Ronnegard and Shen 2015) https://journal.r-project.org/archive/2015/RJ-2015-017/RJ-2015-017.pdf.

Last 30 days

This package has been downloaded 410 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 21 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 5,814 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Sep 11, 2024 with 61 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.