RStan: the R interface to Stan. rstan: User-facing R functions are provided by this package to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the ’StanHeaders’ package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via variational approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.

References in zbMATH (referenced in 68 articles )

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  1. Auerbach, Jonathan; Eshleman, Christopher; Trangucci, Rob: A hierarchical Bayes approach to adjust for selection bias in before-after analyses of vision zero policies (2021)
  2. Dai, Chenguang; Chan, Duo; Huybers, Peter; Pillai, Natesh: Late 19th century navigational uncertainties and their influence on sea surface temperature estimates (2021)
  3. David Issa Mattos, Érika Martins Silva Ramos: Bayesian Paired-Comparison with the bpcs Package (2021) arXiv
  4. Francisco Palmí-Perales, Virgilio Gómez-Rubio, Miguel A. Martinez-Beneito: Bayesian Multivariate Spatial Models for Lattice Data with INLA (2021) not zbMATH
  5. Kelter, Riko: Bayesian model selection in the (\mathcalM)-open setting -- approximate posterior inference and subsampling for efficient large-scale leave-one-out cross-validation via the difference estimator (2021)
  6. Li, Yicheng; Raftery, Adrian E.: Accounting for smoking in forecasting mortality and life expectancy (2021)
  7. Mayrink, V. D., Duarte, J. D. N., Demarqui, F. N.: pexm: A JAGS Module for Applications Involving the Piecewise Exponential Distribution (2021) not zbMATH
  8. Philippe Rast; Stephen Martin: bmgarch: An R-Package for Bayesian Multivariate GARCH models (2021) not zbMATH
  9. Raim, Andrew M.; Holan, Scott H.; Bradley, Jonathan R.; Wikle, Christopher K.: Spatio-temporal change of support modeling with \textttR (2021)
  10. Schramm, Pele; Batchelder, William H.: Hierarchical paired comparison modeling, a cultural consensus theory approach (2021)
  11. Shan, Mingyang; Thomas, Kali S.; Gutman, Roee: A multiple imputation procedure for record linkage and causal inference to estimate the effects of home-delivered meals (2021)
  12. Suchit Mehrotra, Arnab Maity: Variational Inference for Shrinkage Priors: The R package vir (2021) arXiv
  13. Angus McLure, Ben O’Neill, Helen Mayfield, Colleen Lau, Brady McPherson: PoolTestR: An R package for estimating prevalence and regression modelling with pooled samples (2020) arXiv
  14. Anne Philippe, Marie-Anne Vibet: Analysis of Archaeological Phases Using the R Package ArchaeoPhases (2020) not zbMATH
  15. Fuglstad, Geir-Arne; Hem, Ingeborg Gullikstad; Knight, Alexander; Rue, Håvard; Riebler, Andrea: Intuitive joint priors for variance parameters (2020)
  16. Gin, Brian; Sim, Nicholas; Skrondal, Anders; Rabe-Hesketh, Sophia: A dyadic IRT model (2020)
  17. Haaf, Julia M.; Merkle, Edgar C.; Rouder, Jeffrey N.: Do items order? The psychology in IRT models (2020)
  18. Izhar Asael Alonzo Matamoros, Cristian Andres Cruz Torres: varstan: An R package for Bayesian analysis of structured time series models with Stan (2020) arXiv
  19. Jeffrey Pullin, Lyle Gurrin, Damjan Vukcevic: Rater: An R Package for Fitting Statistical Models of Repeated Categorical Ratings (2020) arXiv
  20. Jouni Helske: Efficient Bayesian generalized linear models with time-varying coefficients: The walker package in R (2020) arXiv

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