IBGS: Iterated Block Gibbs Sampler for Ultrahigh-Dimensional Variable
Selection and Model Averaging
Variable selection for generalized linear models and the Cox
proportional-hazards model in ultrahigh dimensions via the iterated block
Gibbs sampler (IBGS). The sampler is implemented in C with parallel block
screening through 'OpenMP', and supports the gaussian, binomial and poisson
families (fitted by least squares or iteratively reweighted least squares)
as well as the Cox model for survival analysis (fitted by its Efron partial
likelihood), together with the AIC, BIC, AICc and extended BIC model
selection criteria.
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