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robmixglm (version 1.2-5)

Robust Generalized Linear Models (GLM) using Mixtures

Description

Robust generalized linear models (GLM) using a mixture method, as described in Beath (2018) . 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.

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Version

Install

install.packages('robmixglm')

Monthly Downloads

5,792

Version

1.2-5

License

GPL (>= 2)

Maintainer

Ken Beath

Last Published

October 31st, 2025

Functions in robmixglm (1.2-5)

print.outlierTest

Print an outlierTest object
robmixglm-package

Fits random effects meta-analysis models including robust models
plot.outlierProbs

Plot outlier probabilities.
predict.robmixglm

Predict Method for robmixglm
AIC

AIC for robmixglm object
outlierTest

Test for the presence of outliers.
summary.robmixglm

summaryficients for robmixglm object
outlierProbs

Calculate outlier probabilities for each observation.
robmixglm

Fits a Robust Generalized Linear Model and Variants
diabdata

Diabetes data
coef

Coefficients for a robmixglm object
BIC

BIC for robmixglm object
residuals.robmixglm

Extract Model Residuals
logLik

log Likelikelihood for robmixglm object
extractAIC

Extract AIC from a Fitted Model
fitted.robmixglm

Fitted values.
hospcosts

Hospital Costs data