Package: robmixglm 1.2-3

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.

Authors:Ken Beath [aut, cre]

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robmixglm/json (API)
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16 exports 0.00 score 20 dependencies 32 scripts 307 downloads

Last updated 2 years agofrom:1b763d73ed. Checks:OK: 9. Indexed: yes.

Exports:AIC.robmixglmBIC.robmixglmcoef.robmixglmextractAIC.robmixglmfitted.robmixglmlogLik.robmixglmoutlierProbsoutlierProbs.robmixglmoutlierTestoutlierTest.robmixglmpredict.robmixglmprint.outlierTestprint.summary.outlierTestrobmixglmsummary.outlierTestsummary.robmixglm

Dependencies:actuarbbmlebdsmatrixbootcodetoolsdigestdoParalleldoRNGexpintfastGHQuadforeachiteratorslatticeMASSMatrixmvtnormnumDerivRcpprngtoolsVGAM