rstanarm

R package rstanarm: Bayesian Applied Regression Modeling via Stan. Estimates pre-compiled regression models using the ’rstan’ package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.


References in zbMATH (referenced in 15 articles )

Showing results 1 to 15 of 15.
Sorted by year (citations)

  1. Izhar Asael Alonzo Matamoros, Cristian Andres Cruz Torres: varstan: An R package for Bayesian analysis of structured time series models with Stan (2020) arXiv
  2. Kowal, Daniel R.; Canale, Antonio: Simultaneous transformation and rounding (STAR) models for integer-valued data (2020)
  3. Riko Kelter: fbst: An R package for the Full Bayesian Significance Test for testing a sharp null hypothesis against its alternative via the e-value (2020) arXiv
  4. Taysseer Sharaf; Theren Williams; Abdallah Chehade; Keshav Pokhrel: BLNN: An R package for training neural networks using Bayesian inference (2020) not zbMATH
  5. Dominique Makowski, Mattan S. Ben-Shachar, Daniel Lüdecke: bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework (2019) not zbMATH
  6. Haziq Jamil, Wicher Bergsma: iprior: An R Package for Regression Modelling using I-priors (2019) arXiv
  7. van Erp, Sara; Oberski, Daniel L.; Mulder, Joris: Shrinkage priors for Bayesian penalized regression (2019)
  8. Adam Peterson, Brisa Sanchez: rstap: An R Package for Spatial Temporal Aggregated Predictor Models (2018) arXiv
  9. Edgar Merkle; Yves Rosseel: blavaan: Bayesian Structural Equation Models via Parameter Expansion (2018) not zbMATH
  10. Massoni, Sébastien; Roux, Nicolas: Optimal group decision: a matter of confidence calibration (2017)
  11. Paul-Christian Bürkner: brms: An R Package for Bayesian Multilevel Models Using Stan (2017) not zbMATH
  12. Quentin F. Gronau, Henrik Singmann, Eric-Jan Wagenmakers: bridgesampling: An R Package for Estimating Normalizing Constants (2017) arXiv
  13. Vehtari, Aki; Gelman, Andrew; Gabry, Jonah: Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC (2017)
  14. Daniel F. Schmidt, Enes Makalic: High-Dimensional Bayesian Regularised Regression with the BayesReg Package (2016) arXiv
  15. Xavier Fernández-i-Marín: ggmcmc: Analysis of MCMC Samples and Bayesian Inference (2016) not zbMATH