robmixglm
Robust Generalized Linear Models (GLM) using Mixtures
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.
- Version1.2-4
- R version≥ 3.2.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release09/27/2024
Documentation
Team
Ken Beath
MaintainerShow author details
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Last 30 days
This package has been downloaded 251 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 14 times.
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Last 365 days
This package has been downloaded 3,996 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jul 21, 2024 with 72 downloads.
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Dependencies
- Imports11 packages
- Suggests4 packages
- Linking To1 package