Stan
Stan: A C++ Library for Probability and Sampling. Stan is a probabilistic programming language implementing full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized maximum likelihood estimation with Optimization (BFGS). Stan is coded in C++ and runs on all major platforms.
Keywords for this software
References in zbMATH (referenced in 174 articles , 1 standard article )
Showing results 1 to 20 of 174.
Sorted by year (- Andrade, Daniel; Takeda, Akiko; Fukumizu, Kenji: Robust Bayesian model selection for variable clustering with the Gaussian graphical model (2020)
- 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
- Chenguang Wang, Elizabeth Colantuoni, Andrew Leroux, Daniel O. Scharfstein: idem: An R Package for Inferences in Clinical Trials with Death and Missingness (2020) not zbMATH
- Cho, Sun-Joo; Brown-Schmidt, Sarah; De Boeck, Paul; Shen, Jianhong: Modeling intensive polytomous time-series eye-tracking data: a dynamic tree-based item response model (2020)
- Fisher, Christopher R.; Houpt, Joseph W.; Gunzelmann, Glenn: Developing memory-based models of ACT-R within a statistical framework (2020)
- Fouskakis, D.; Petrakos, G.; Rotous, I.: A Bayesian longitudinal model for quantifying students’ preferences regarding teaching quality indicators (2020)
- Izhar Asael Alonzo Matamoros, Cristian Andres Cruz Torres: varstan: An R package for Bayesian analysis of structured time series models with Stan (2020) arXiv
- Jacob Leander, Joachim Almquist, Anna Johnning, Julia Larsson, Mats Jirstrand: NLMEModeling: A Wolfram Mathematica Package for Nonlinear Mixed Effects Modeling of Dynamical Systems (2020) arXiv
- Jauch, Michael; Hoff, Peter D.; Dunson, David B.: Random orthogonal matrices and the Cayley transform (2020)
- Jeffrey Pullin, Lyle Gurrin, Damjan Vukcevic: Rater: An R Package for Fitting Statistical Models of Repeated Categorical Ratings (2020) arXiv
- Jouni Helske: Efficient Bayesian generalized linear models with time-varying coefficients: The walker package in R (2020) arXiv
- Karimi, Belhal; Lavielle, Marc; Moulines, Eric: f-SAEM: a fast stochastic approximation of the EM algorithm for nonlinear mixed effects models (2020)
- Lijoi, Antonio; Prünster, Igor; Rigon, Tommaso: Sampling hierarchies of discrete random structures (2020)
- Li, Yicheng; Raftery, Adrian E.: Estimating and forecasting the smoking-attributable mortality fraction for both genders jointly in over 60 countries (2020)
- Ma, Zhihua; Chen, Guanghui: Bayesian semiparametric latent variable model with DP prior for joint analysis: implementation with nimble (2020)
- Michalkiewicz, Martha; Horn, Sebastian S.; Bayen, Ute J.: Hierarchical multinomial modeling to explain individual differences in children’s clustering in free recall (2020)
- Miller, David L.; Glennie, Richard; Seaton, Andrew E.: Understanding the stochastic partial differential equation approach to smoothing (2020)
- Moores, Matthew; Nicholls, Geoff; Pettitt, Anthony; Mengersen, Kerrie: Scalable Bayesian inference for the inverse temperature of a hidden Potts model (2020)
- Mulder, Kees; Klugkist, Irene; van Renswoude, Daan; Visser, Ingmar: Mixtures of peaked power Batschelet distributions for circular data with application to saccade directions (2020)
- Oliver Schulz, Frederik Beaujean, Allen Caldwell, Cornelius Grunwald, Vasyl Hafych, Kevin Kröninger, Salvatore La Cagnina, Lars Röhrig, Lolian Shtembari: BAT.jl - A Julia-based tool for Bayesian inference (2020) arXiv