Robust generalized linear models (GLM) using a mixture method, as described in Beath (2018) <doi:10.1080/02664763.2017.1414164>. This assumes that the data are a mixture of standard observations, being a generalised linear model, and outlier observations from an overdispersed generalized linear model. The overdispersed linear model is obtained by including a normally distributed random effect in the linear predictor of the generalized linear model.
Version: 1.2-4 Depends: R (≥ 3.2.0) Imports: fastGHQuad, stats, bbmle, VGAM, actuar, Rcpp (≥ 0.12.15), methods, boot, numDeriv, parallel, doParallel, foreach, doRNG, MASS LinkingTo: Rcpp Suggests: R.rsp, robustbase, lattice, forward Published: 2024-09-27 DOI: 10.32614/CRAN.package.robmixglm Author: Ken Beath [aut, cre] Maintainer: Ken Beath <ken at kjbeath.id.au> Contact: Ken Beath <ken@kjbeath.id.au> License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] NeedsCompilation: yes Materials: NEWS CRAN checks: robmixglm results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=robmixglm to link to this page.
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