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: | 1.1-0 |
| Depends: | R (≥ 3.2.0) |
| Imports: | fastGHQuad, stats, bbmle, MASS, VGAM, actuar, Rcpp (≥ 0.12.15), methods, boot, numDeriv, parallel, doParallel, foreach, doRNG |
| LinkingTo: | Rcpp |
| Suggests: | R.rsp, robustbase, lattice, forward |
| Published: | 2020-06-18 |
| Author: | Ken Beath [aut, cre] |
| Maintainer: | Ken Beath <ken.beath at mq.edu.au> |
| Contact: | Ken Beath <ken.beath@mq.edu.au> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | robmixglm results |
| Reference manual: | robmixglm.pdf |
| Vignettes: |
robmixglm: An R Package for the Analysis of Robust Generalized Linear Models |
| Package source: | robmixglm_1.1-0.tar.gz |
| Windows binaries: | r-devel: robmixglm_1.1-0.zip, r-release: robmixglm_1.1-0.zip, r-oldrel: robmixglm_1.1-0.zip |
| macOS binaries: | r-release: robmixglm_1.1-0.tgz, r-oldrel: robmixglm_1.1-0.tgz |
| Old sources: | robmixglm archive |
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