R package nimble: Flexible BUGS-Compatible System for Hierarchical Statistical Modeling and Algorithm Development. Flexible application of algorithms to models specified in the BUGS language. Algorithms can be written in the NIMBLE language and made available to any model.

References in zbMATH (referenced in 26 articles , 1 standard article )

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  1. Campbell, Harlan; De Valpine, Perry; Maxwell, Lauren; De Jong, Valentijn M. T.; Debray, Thomas P. A.; Jaenisch, Thomas; Gustafson, Paul: Bayesian adjustment for preferential testing in estimating infection fatality rates, as motivated by the COVID-19 pandemic (2022)
  2. Bonner, S., Kim, H.-N., Westneat, D., Mutzel, A., Wright, J., Schofield, M.: dalmatian: A Package for Fitting Double Hierarchical Linear Models in R via JAGS and nimble (2021) not zbMATH
  3. Hepler, Staci A.; Waller, Lance A.; Kline, David M.: A multivariate spatiotemporal change-point model of opioid overdose deaths in Ohio (2021)
  4. Jeffrey W. Doser, Andrew O. Finley, Marc Kery, Elise F. Zipkin: spOccupancy: An R package for single species, multispecies, and integrated spatial occupancy models (2021) arXiv
  5. Lawson, Andrew B.: Using R for Bayesian spatial and spatio-temporal health modeling (2021)
  6. Martins, Rui; Caldeira, Jorge; Lopes, Inês; João Mendes, José: Improving teeth aesthetics using a spatially shared-parameters model for independent regular lattices (2021)
  7. Ma, Zhihua; Chen, Guanghui: Bayesian joint analysis using a semiparametric latent variable model with non-ignorable missing covariates for CHNS data (2021)
  8. Michaud, N., de Valpine, P., Turek, D., Paciorek, C. J., Nguyen, D.: Sequential Monte Carlo Methods in the nimble and nimbleSMC R Packages (2021) not zbMATH
  9. Nemeth, Christopher; Fearnhead, Paul: Stochastic gradient Markov chain Monte Carlo (2021)
  10. Perry de Valpine, Sally Paganin, Daniel Turek: compareMCMCs: An R package for studying MCMC efficiency (2021) not zbMATH
  11. Raim, Andrew M.; Holan, Scott H.; Bradley, Jonathan R.; Wikle, Christopher K.: Spatio-temporal change of support modeling with \textttR (2021)
  12. Rodríguez, Carlos E.; Walker, Stephen G.: Copula particle filters (2021)
  13. Wang, Zhenxun; Lin, Lifeng; Murray, Thomas; Hodges, James S.; Chu, Haitao: Bridging randomized controlled trials and single-arm trials using commensurate priors in arm-based network meta-analysis (2021)
  14. Ma, Zhihua; Chen, Guanghui: Bayesian semiparametric latent variable model with DP prior for joint analysis: implementation with nimble (2020)
  15. Nguyen, Dao; de Valpine, Perry; Atchade, Yves; Turek, Daniel; Michaud, Nicholas; Paciorek, Christopher: Nested adaptation of MCMC algorithms (2020)
  16. Risser, Mark D.; Turek, Daniel: Bayesian inference for high-dimensional nonstationary Gaussian processes (2020)
  17. Stoner, Oliver; Economou, Theo: An advanced hidden Markov model for hourly rainfall time series (2020)
  18. Amaral Turkman, Maria Antónia; Paulino, Carlos Daniel; Müller, Peter: Computational Bayesian statistics. An introduction (2019)
  19. Daniel Turek, Mark Risser: Bayesian nonstationary Gaussian process modeling: the BayesNSGP package for R (2019) arXiv
  20. Finke, Axel; King, Ruth; Beskos, Alexandros; Dellaportas, Petros: Efficient sequential Monte Carlo algorithms for integrated population models (2019)

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