R package hglm: Hierarchical Generalized Linear Models. 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.
Keywords for this software
References in zbMATH (referenced in 6 articles , 1 standard article )
Showing results 1 to 6 of 6.
- Noh, Maengseok; Lee, Youngjo; Oud, Johan H. L.; Toharudin, Toni: Hierarchical likelihood approach to non-Gaussian factor analysis (2019)
- Lars Rönnegård, Xia Shen, Moudud Alam: hglm: A Package for Fitting Hierarchical Generalized Linear Models (2018) not zbMATH
- Lee, Youngjo; Ronnegård, Lars; Noh, Maengseok: Data analysis using hierarchical generalized linear models with R (2017)
- Wolny-Dominiak, Alicja: Bootstrap mean squared error of prediction in loss reserving (2017)
- Hyungsuk Tak, Joseph Kelly, Carl N. Morris: Rgbp: An R Package for Gaussian, Poisson, and Binomial Random Effects Models with Frequency Coverage Evaluations (2016) arXiv
- Rieck, Konrad; Wressnegger, Christian: Harry: a tool for measuring string similarity (2016)