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 26 articles )

Showing results 1 to 20 of 26.
Sorted by year (citations)

1 2 next

  1. Daniel Lüdecke, Dominique Makowski, Philip Waggoner, Mattan S. Ben-Shachar: see: An R Package for Visualizing Statistical Models (2021) not zbMATH
  2. David Issa Mattos, Érika Martins Silva Ramos: Bayesian Paired-Comparison with the bpcs Package (2021) arXiv
  3. James A. Scott, Axel Gandy, Swapnil Mishra, Samir Bhatt, Seth Flaxman, H. Juliette T. Unwin, Jonathan Ish-Horowicz: Epidemia: An R Package for Semi-Mechanistic Bayesian Modelling of Infectious Diseases using Point Processes (2021) arXiv
  4. Merkle, E. C., Fitzsimmons, E., Uanhoro, J., Goodrich, B. : Efficient Bayesian Structural Equation Modeling in Stan (2021) not zbMATH
  5. Ryan Hornby, Jingchen Hu: Bayesian Estimation of Attribute Disclosure Risks in Synthetic Data with the AttributeRiskCalculation R Package (2021) arXiv
  6. Wollschläger, Daniel: R compact. The fast introduction into data analysis (2021)
  7. Alkhairy, Ibrahim; Low-Choy, Samantha; Murray, Justine; Wang, Junhu; Pettitt, Anthony: Quantifying conditional probability tables in Bayesian networks: Bayesian regression for scenario-based encoding of elicited expert assessments on feral pig habitat (2020)
  8. Altinisik, Yasin: A comparative study on the performance of frequentist and Bayesian estimation methods under separation in logistic regression (2020)
  9. Izhar Asael Alonzo Matamoros, Cristian Andres Cruz Torres: varstan: An R package for Bayesian analysis of structured time series models with Stan (2020) arXiv
  10. Kowal, Daniel R.; Canale, Antonio: Simultaneous transformation and rounding (STAR) models for integer-valued data (2020)
  11. Piironen, Juho; Paasiniemi, Markus; Vehtari, Aki: Projective inference in high-dimensional problems: prediction and feature selection (2020)
  12. 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
  13. Taysseer Sharaf; Theren Williams; Abdallah Chehade; Keshav Pokhrel: BLNN: An R package for training neural networks using Bayesian inference (2020) not zbMATH
  14. Tomás Capretto, Camen Piho, Ravin Kumar, Jacob Westfall, Tal Yarkoni, Osvaldo A. Martin: Bambi: A simple interface for fitting Bayesian linear models in Python (2020) arXiv
  15. Zhang, Chelsea; Taylor, Sean J.; Cobb, Curtiss; Sekhon, Jasjeet: Active matrix factorization for surveys (2020)
  16. Dominique Makowski, Mattan S. Ben-Shachar, Daniel Lüdecke: bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework (2019) not zbMATH
  17. Haziq Jamil, Wicher Bergsma: iprior: An R Package for Regression Modelling using I-priors (2019) arXiv
  18. van Erp, Sara; Oberski, Daniel L.; Mulder, Joris: Shrinkage priors for Bayesian penalized regression (2019)
  19. Adam Peterson, Brisa Sanchez: rstap: An R Package for Spatial Temporal Aggregated Predictor Models (2018) arXiv
  20. Edgar Merkle; Yves Rosseel: blavaan: Bayesian Structural Equation Models via Parameter Expansion (2018) not zbMATH

1 2 next