abc

abc: Tools for Approximate Bayesian Computation (ABC). Implements several ABC algorithms for performing parameter estimation, model selection, and goodness-of-fit. Cross-validation tools are also available for measuring the accuracy of ABC estimates, and to calculate the misclassification probabilities of different models.


References in zbMATH (referenced in 40 articles )

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  1. Dmitrieva, Tatiana; McCullough, Kristin; Ebrahimi, Nader: Improved approximate Bayesian computation methods via empirical likelihood (2021)
  2. Billig Rose, Erica; Roy, Jason A.; Castillo-Neyra, Ricardo; Ross, Michelle E.; Condori-Pino, Carlos; Peterson, Jennifer K.; Naquira-Velarde, Cesar; Levy, Michael Z.: A real-time search strategy for finding urban disease vector infestations (2020)
  3. Jhwueng, Dwueng-Chwuan: Modeling rate of adaptive trait evolution using Cox-Ingersoll-Ross process: an approximate Bayesian computation approach (2020)
  4. Thong, David; Streftaris, George; Gibson, Gavin J.: Latent likelihood ratio tests for assessing spatial kernels in epidemic models (2020)
  5. Griswold, Cortland K.: An ancestral process with selection in an ecological community (2019)
  6. Ke, Yuqin; Tian, Tianhai: Approximate Bayesian computational methods for the inference of unknown parameters (2019)
  7. Kobayashi, Genya; Kakamu, Kazuhiko: Approximate Bayesian computation for Lorenz curves from grouped data (2019)
  8. Koblents, Eugenia; Mariño, Inés P.; Míguez, Joaquín: Bayesian computation methods for inference in stochastic kinetic models (2019)
  9. Lee, Jeong Eun; Nicholls, Geoff K.; Ryder, Robin J.: Calibration procedures for approximate Bayesian credible sets (2019)
  10. Maire, Florian; Friel, Nial; Alquier, Pierre: Informed sub-sampling MCMC: approximate Bayesian inference for large datasets (2019)
  11. Ziwen An, Leah F. South, Christopher C. Drovand: BSL: An R Package for Efficient Parameter Estimation for Simulation-Based Models via Bayesian Synthetic Likelihood (2019) arXiv
  12. Ho, Lam Si Tung; Crawford, Forrest W.; Suchard, Marc A.: Direct likelihood-based inference for discretely observed stochastic compartmental models of infectious disease (2018)
  13. Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W.; Minin, Vladimir N.; Suchard, Marc A.: Birth/birth-death processes and their computable transition probabilities with biological applications (2018)
  14. Karabatsos, George; Leisen, Fabrizio: An approximate likelihood perspective on ABC methods (2018)
  15. Lambert, Ben; MacLean, Adam L.; Fletcher, Alexander G.; Combes, Alexander N.; Little, Melissa H.; Byrne, Helen M.: Bayesian inference of agent-based models: a tool for studying kidney branching morphogenesis (2018)
  16. McKinley, Trevelyan J.; Vernon, Ian; Andrianakis, Ioannis; McCreesh, Nicky; Oakley, Jeremy E.; Nsubuga, Rebecca N.; Goldstein, Michael; White, Richard G.: Approximate Bayesian computation and simulation-based inference for complex stochastic epidemic models (2018)
  17. Nott, David J.; Drovandi, Christopher C.; Mengersen, Kerrie; Evans, Michael: Approximation of Bayesian predictive (p)-values with regression ABC (2018)
  18. Skvortsov, Alex; Ristic, Branko; Kamenev, Alex: Predicting population extinction from early observations of the Lotka-Volterra system (2018)
  19. Spantini, Alessio; Bigoni, Daniele; Marzouk, Youssef: Inference via low-dimensional couplings (2018)
  20. Dennis Prangle: gk: An R Package for the g-and-k and generalised g-and-h Distributions (2017) arXiv

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