spikeSlabGAM

R package spikeSlabGAM: Bayesian variable selection and model choice for generalized additive mixed models. Bayesian variable selection, model choice, and regularized estimation for (spatial) generalized additive mixed regression models via SSVS with spike-and-slab priors.

Keywords for this software

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References in zbMATH (referenced in 8 articles , 1 standard article )

Showing results 1 to 8 of 8.
Sorted by year (citations)

  1. Robin Genuer, Jean-Michel Poggi, Christine Tuleau-Malot: VSURF: An R Package for Variable Selection Using Random Forests (2015) not zbMATH
  2. Goldsmith, Jeff; Scheipl, Fabian: Estimator selection and combination in scalar-on-function regression (2014)
  3. Yuan, J.; Wei, G.: An efficient Monte Carlo EM algorithm for Bayesian Lasso (2014)
  4. Lykou, Anastasia; Ntzoufras, Ioannis: On Bayesian lasso variable selection and the specification of the shrinkage parameter (2013)
  5. Scheipl, Fabian; Kneib, Thomas; Fahrmeir, Ludwig: Penalized likelihood and Bayesian function selection in regression models (2013)
  6. Lesaffre, Emmanuel; Lawson, Andrew B.: Bayesian biostatistics (2012)
  7. Scheipl, Fabian; Fahrmeir, Ludwig; Kneib, Thomas: Spike-and-slab priors for function selection in structured additive regression models (2012)
  8. Fabian Scheipl: spikeSlabGAM: Bayesian Variable Selection, Model Choice and Regularization for Generalized Additive Mixed Models in R (2011) not zbMATH